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125 Commits
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Jade Choghari
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7176e06b52
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Add TextNet (#34979)
* WIP * Add config and modeling for Fast model * Refactor modeling and add tests * More changes * WIP * Add tests * Add conversion script * Add conversion scripts, integration tests, image processor * Fix style and copies * Add fast model to init * Add fast model in docs and other places * Fix import of cv2 * Rename image processing method * Fix build * Fix Build * fix style and fix copies * Fix build * Fix build * Fix Build * Clean up docstrings * Fix Build * Fix Build * Fix Build * Fix build * Add test for image_processing_fast and add documentation tests * some refactorings * Fix failing tests * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Introduce TextNet * Fix failures * Refactor textnet model * Fix failures * Add cv2 to setup * Fix failures * Fix failures * Add CV2 dependency * Fix bugs * Fix build issue * Fix failures * Remove textnet from modeling fast * Fix build and other things * Fix build * some cleanups * some cleanups * Some more cleanups * Fix build * Incorporate PR feedbacks * More cleanup * More cleanup * More cleanup * Fix build * Remove all the references of fast model * More cleanup * Fix build * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Fix Build * Fix build * Fix build * Fix build * Fix build * Fix build * Incorporate PR feedbacks * Fix style * Fix build * Incorporate PR feedbacks * Fix image processing mean and std * Incorporate PR feedbacks * fix build failure * Add assertion to image processor * Incorporate PR feedbacks * Incorporate PR feedbacks * fix style failures * fix build * Fix Imageclassification's linear layer, also introduce TextNetImageProcessor * Fix build * Fix build * Fix build * Fix build * Incorporate PR feedbacks * Incorporate PR feedbacks * Fix build * Incorporate PR feedbacks * Remove some script * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Incorporate PR feedbacks * Fix image processing in textnet * Incorporate PR Feedbacks * Fix CI failures * Fix failing test * Fix failing test * Fix failing test * Fix failing test * Fix failing test * Fix failing test * Add textnet to readme * Improve readability * Incorporate PR feedbacks * fix code style * fix key error and convert working * tvlt shouldn't be here * fix test modeling test * Fix tests, make fixup * Make fixup * Make fixup * Remove TEXTNET_PRETRAINED_MODEL_ARCHIVE_LIST * improve type annotation Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update tests/models/textnet/test_image_processing_textnet.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * improve type annotation Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * space typo Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * improve type annotation Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update src/transformers/models/textnet/configuration_textnet.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * make conv layer kernel sizes and strides default to None * Update src/transformers/models/textnet/modeling_textnet.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update src/transformers/models/textnet/modeling_textnet.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * fix keyword bug * add batch init and make fixup * Make fixup * Update integration test * Add figure * Update textnet.md * add testing and fix errors (classification, imgprocess) * fix error check * make fixup * make fixup * revert to original docstring * add make style * remove conflict for now * Update modeling_auto.py got a confusion in `timm_wrapper` - was giving some conflicts * Update tests/models/textnet/test_modeling_textnet.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update src/transformers/models/textnet/modeling_textnet.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update tests/models/textnet/test_modeling_textnet.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update src/transformers/models/textnet/modeling_textnet.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * add changes * Update textnet.md * add doc * add authors hf ckpt + rename * add feedback: classifier/docs --------- Co-authored-by: raghavanone <opensourcemaniacfreak@gmail.com> Co-authored-by: jadechoghari <jadechoghari@users.noreply.huggingface.co> Co-authored-by: Niels <niels.rogge1@gmail.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> |
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松本和真
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96bf3d6cc5
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Add diffllama (#34083)
* first adding diffllama * add Diff Attention and other but still with errors * complate make attention Diff-Attention * fix some bugs which may be caused by transformer-cli while adding model * fix a bug caused by forgetting KV cache... * Update src/transformers/models/diffllama/modeling_diffllama.py You don't need to divide by 2 if we use same number of attention heads as llama. instead you can just split in forward. Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py fit to changeing "num_heads // 2" place Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py new codes are more meaningful than before Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py new codes are more meaningful than before Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py fit to changeing "num_heads // 2" place Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py fix 2times divide by sqrt(self.head_dim) Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py fix 2times divide by sqrt(self.head_dim) Co-authored-by: Minho Ryu <ryumin93@gmail.com> * Update src/transformers/models/diffllama/modeling_diffllama.py fit to changeing "num_heads // 2" place. and more visible Co-authored-by: Minho Ryu <ryumin93@gmail.com> * I found Attention missed implemented from paper still on |
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NielsRogge
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6e0515e99c
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Add DINOv2 with registers (#35348)
* added changes from 32905 * fixed mistakes caused by select all paste * rename diff_dinov2... * ran tests * Fix modular * Fix tests * Use new init * Simplify drop path * Convert all checkpoints * Add figure and summary * Update paths * Update docs * Update docs * Update toctree * Update docs --------- Co-authored-by: BernardZach <bernardzach00@gmail.com> Co-authored-by: Zach Bernard <132859071+BernardZach@users.noreply.github.com> |
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Benjamin Warner
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667ed5635e
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Add ModernBERT to Transformers (#35158)
* initial cut of modernbert for transformers
* small bug fixes
* fixes
* Update import
* Use compiled mlp->mlp_norm to match research implementation
* Propagate changes in modular to modeling
* Replace duplicate attn_out_dropout in favor of attention_dropout
cc @warner-benjamin let me know if the two should remain separate!
* Update BOS to CLS and EOS to SEP
Please confirm @warner-benjamin
* Set default classifier bias to False, matching research repo
* Update tie_word_embeddings description
* Fix _init_weights for ForMaskedLM
* Match base_model_prefix
* Add compiled_head to match research repo outputs
* Fix imports for ModernBertForMaskedLM
* Just use "gelu" default outright for classifier
* Fix config name typo: initalizer -> initializer
* Remove some unused parameters in docstring. Still lots to edit there!
* Compile the embeddings forward
Not having this resulted in very slight differences - so small it wasn't even noticed for the base model, only for the large model.
But the tiny difference for large propagated at the embedding layer through the rest of the model, leading to notable differences of ~0.0084 average per value, up to 0.2343 for the worst case.
* Add drafts for ForSequenceClassification/ForTokenClassification
* Add initial SDPA support (not exactly equivalent to FA2 yet!)
During testing, FA2 and SDPA still differ by about 0.0098 per value in the token embeddings. It still predicts the correct mask fills, but I'd like to get it fully 1-1 if possible.
* Only use attention dropout if training
* Add initial eager attention support (also not equivalent to FA2 yet!)
Frustratingly, I also can't get eager to be equivalent to FA2 (or sdpa), but it does get really close, i.e. avg ~0.010 difference per value.
Especially if I use fp32 for both FA2&eager, avg ~0.0029 difference per value
The fill-mask results are good with eager.
* Add initial tests, output_attentions, output_hidden_states, prune_heads
Tests are based on BERT, not all tests pass yet: 23 failed, 79 passed, 100 skipped
* Remove kwargs from ModernBertForMaskedLM
Disable sparse_prediction by default to match the normal HF, can be enabled via config
* Remove/adjust/skip improper tests; warn if padding but no attn mask
* Run formatting etc.
* Run python utils/custom_init_isort.py
* FlexAttention with unpadded sequences(matches FA2 within bf16 numerics)
* Reformat init_weights based on review
* self -> module in attention forwards
* Remove if config.tie_word_embeddings
* Reformat output projection on a different line
* Remove pruning
* Remove assert
* Call contiguous() to simplify paths
* Remove prune_qkv_linear_layer
* Format code
* Keep as kwargs, only use if needed
* Remove unused codepaths & related config options
* Remove 3d attn_mask test; fix token classification tuple output
* Reorder: attention_mask above position_ids, fixes gradient checkpointing
* Fix usage if no FA2 or torch v2.5+
* Make torch.compile/triton optional
Should we rename 'compile'? It's a bit vague
* Separate pooling options into separate functions (cls, mean) - cls as default
* Simplify _pad_modernbert_output, remove unused labels path
* Update tied weights to remove decoder.weight, simplify decoder loading
* Adaptively set config.compile based on hf_device_map/device/resize, etc.
* Update ModernBertConfig docstring
* Satisfy some consistency checks, add unfinished docs
* Only set compile to False if there's more than 1 device
* Add docstrings for public ModernBert classes
* Dont replace docstring returns - ends up being duplicate
* Fix mistake in toctree
* Reformat toctree
* Patched FlexAttention, SDPA, Eager with Local Attention
* Implement FA2 -> SDPA -> Eager attn_impl defaulting, crucial
both to match the original performance, and to get the highest inference speed without requiring users to manually pick FA2
* Patch test edge case with Idefics3 not working with 'attn_implementation="sdpa"'
* Repad all_hidden_states as well
* rename config.compile to reference_compile
* disable flex_attention since it crashes
* Update modernbert.md
* Using dtype min to mask in eager
* Fully remove flex attention for now
It's only compatible with the nightly torch 2.6, so we'll leave it be for now. It's also slower than eager/sdpa.
Also, update compile -> reference_compile in one more case
* Call contiguous to allow for .view()
* Copyright 2020 -> 2024
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update/simplify __init__ structure
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Remove "... if dropout_prob > 0 else identity"
As dropout with 0.0 should be efficient like identity
* re-use existing pad/unpad functions instead of creating new ones
* remove flexattention method
* Compute attention_mask and local_attention_mask once in modeling
* Simplify sequence classification prediction heads, only CLS now
Users can make custom heads if they feel like it
Also removes the unnecessary pool parameter
* Simplify module.training in eager attn
* Also export ModernBertPreTrainedModel
* Update the documentation with links to finetuning scripts
* Explain local_attention_mask parameter in docstring
* Simplify _autoset_attn_implementation, rely on super()
* Keep "in" to initialize Prediction head
Doublechecked with Benjamin that it's correct/what we used for pretraining
* add back mean pooling
* Use the pooling head in TokenClassification
* update copyright
* Reset config._attn_implementation_internal on failure
* Allow optional attention_mask in ForMaskedLM head
* fix failing run_slow tests
* Add links to the paper
* Remove unpad_no_grad, always pad/unpad without gradients
* local_attention_mask -> sliding_window_mask
* Revert "Use the pooling head in TokenClassification"
This reverts commit
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Yu Chin Fabian Lim
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9613933b02
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Add the Bamba Model (#34982)
* initial commit for PR Co-authored-by: Gabe Goodhart <gabe.l.hart@gmail.com> * rename dynamic cache Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * add more unit tests Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * add integration test Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * add integration test Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * Add modular bamba file * Remove trainer changes from unrelated PR * Modify modular and cofig to get model running * Fix some CI errors and beam search * Fix a plethora of bugs from CI/docs/etc * Add bamba to models with special caches * Updat to newer mamba PR for mamba sublayer * fix test_left_padding_compatibility Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * fix style Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * fix remaining tests Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * missed this test Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * ran make style Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * move slow tag to integration obj Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * make style Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * address comments Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * fix modular Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * left out one part of modular Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * change model Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * Make Rotary modular as well * Update bamba.md Added overview, update Model inference card and added config * Update bamba.md * Update bamba.md * Update bamba.md Minor fixes * Add docs for config and model back Signed-off-by: Antoni Viros i Martin <aviros@ibm.com> * Add warning when using fast kernels * replaced generate example Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> * Address comments from PR Signed-off-by: Antoni Viros i Martin <aviros@ibm.com> * Propagate attention fixes Signed-off-by: Antoni Viros i Martin <aviros@ibm.com> * Fix attention interfaces to the new API Signed-off-by: Antoni Viros i Martin <aviros@ibm.com> * Fix API for decoder layer Signed-off-by: Antoni Viros i Martin <aviros@ibm.com> * Remove extra weights Signed-off-by: Antoni Viros i Martin <aviros@ibm.com> --------- Signed-off-by: Yu Chin Fabian Lim <flim@sg.ibm.com> Signed-off-by: Antoni Viros i Martin <aviros@ibm.com> Co-authored-by: Gabe Goodhart <gabe.l.hart@gmail.com> Co-authored-by: Antoni Viros i Martin <aviros@ibm.com> Co-authored-by: divya-kumari32 <72085811+divya-kumari32@users.noreply.github.com> Co-authored-by: Antoni Viros <ani300@gmail.com> |
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Billel Mokeddem
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6c08b3b6e5
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Add Falcon3 documentation (#35307)
* Add Falcon3 documentation * Update Falcon3 documentation * Change Falcon to Falcon3 * Update docs and run make fix-copies * Add blog post and huggingface models links |
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Tony Wu
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f33a0cebb3
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Add ColPali to 🤗 transformers (#33736)
* feat: run `add-new-model-like` * feat: add paligemma code with "copied from" * feat: add ColPaliProcessor * feat: add ColPaliModel * feat: add ColPaliConfig * feat: rename `ColPaliForConditionalGeneration` to `ColPaliModel` * fixup modeling colpali * fix: fix root import shortcuts * fix: fix `modeling_auto` dict * feat: comment out ColPali test file * fix: fix typos from `add-new-model-like` * feat: explicit the forward input args * feat: move everything to `modular_colpali.py` * fix: put back ColPaliProcesor * feat: add auto-generated files * fix: run `fix-copies` * fix: remove DOCStRING constants to make modular converter work * fix: fix typo + modular converter * fix: add missing imports * feat: no more errors when loading ColPaliModel * fix: remove unused args in forward + tweak doc * feat: rename `ColPaliModel` to `ColPaliForRetrieval` * fix: apply `fix-copies` * feat: add ColPaliProcessor to `modular_colpali` * fix: run make quality + make style * fix: remove duplicate line in configuration_auto * feat: make ColPaliModel inehrit from PaliGemmaForConditionalGeneration * fix: tweak and use ColPaliConfig * feat: rename `score` to `post_process_retrieval` * build: run modular formatter + make style * feat: convert colpali weights + fixes * feat: remove old weight converter file * feat: add and validate tests * feat: replace harcoded path to "vidore/colpali-v1.2-hf" in tests * fix: add bfloat16 conversion in weight converter * feat: replace pytest with unittest in modeling colpali test * feat: add sanity check for weight conversion (doesn't work yet) * feat: add shape sanity check in weigth converter * feat: make ColPaliProcessor args explicit * doc: add doc for ColPali * fix: trying to fix output mismatch * feat: tweaks * fix: ColPaliModelOutput inherits from ModelOutput instead of PaliGemmaCausalLMOutputWithPast * fix: address comments on PR * fix: adapt tests to the Hf norm * wip: try things * feat: add `__call__` method to `ColPaliProcessor` * feat: remove need for dummy image in `process_queries` * build: run new modular converter * fix: fix incorrect method override * Fix tests, processing, modular, convert * fix tokenization auto * hotfix: manually fix processor -> fixme once convert modular is fixed * fix: convert weights working * feat: rename and improve convert weight script * feat: tweaks * fest: remove `device` input for `post_process_retrieval` * refactor: remove unused `get_torch_device` * Fix all tests * docs: update ColPali model doc * wip: fix convert weights to hf * fix logging modular * docs: add acknowledgements in model doc * docs: add missing docstring to ColPaliProcessor * docs: tweak * docs: add doc for `ColPaliForRetrievalOutput.forward` * feat: add modifications from colpali-engine v0.3.2 in ColPaliProcessor * fix: fix and upload colapli hf weights * refactor: rename `post_process_retrieval` to `score_retrieval` * fix: fix wrong typing for `score_retrieval` * test: add integration test for ColPali * chore: rerun convert modular * build: fix root imports * Update docs/source/en/index.md Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com> * fix: address PR comments * wip: reduce the prediction gap in weight conversion * docs: add comment in weight conversion script * docs: add example for `ColPaliForRetrieval.forward` * tests: change dataset path to the new one in hf-internal * fix: colpali weight conversion works * test: add fine-grained check for ColPali integration test * fix: fix typos in convert weight script * docs: move input docstring in a variable * fix: remove hardcoded torch device in test * fix: run the new modular refactor * docs: fix python example for ColPali * feat: add option to choose `score_retrieval`'s output dtype and device * docs: update doc for `score_retrieval` * feat: add `patch_size` property in ColPali model * chore: run `make fix-copies` * docs: update description for ColPali cookbooks * fix: remove `ignore_index` methods * feat: remove non-transformers specific methods * feat: update `__init__.py` to new hf format * fix: fix root imports in transformers * feat: remove ColPali's inheritance from PaliGemma * Fix CI issues * nit remove prints * feat: remove ColPali config and model from `modular_colpali.py` * feat: add `ColPaliPreTrainedModel` and update modeling and configuration code * fix: fix auto-removed imports in root `__init__.py` * fix: various fixes * fix: fix `_init_weight` * temp: comment `AutoModel.from_config` for experiments * fix: add missing `output_attentions` arg in ColPali's forward * fix: fix `resize_token_embeddings` * fix: make `input_ids` optional in forward * feat: rename `projection_layer` to `embedding_proj_layer` * wip: fix convert colpali weight script * fix tests and convert weights from original repo * fix unprotected import * fix unprotected torch import * fix style * change vlm_backbone_config to vlm_config * fix unprotected import in modular this time * fix: load config from Hub + tweaks in convert weight script * docs: move example usage from model docstring to model markdown * docs: fix input docstring for ColPali's forward method * fix: use `sub_configs` for ColPaliConfig * fix: remove non-needed sanity checks in weight conversion script + tweaks * fix: fix issue with `replace_return_docstrings` in ColPali's `forward` * docs: update docstring for `ColPaliConfig` * test: change model path in ColPali test * fix: fix ColPaliConfig * fix: fix weight conversion script * test: fix expected weights for ColPali model * docs: update ColPali markdown * docs: fix minor typo in ColPaliProcessor * Fix tests and add _no_split_modules * add text_config to colpali config * [run slow] colpali * move inputs to torch_device in integration test * skip test_model_parallelism * docs: clarify quickstart snippet in ColPali's model card * docs: update ColPali's model card --------- Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co> Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com> |
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alexrs-cohere
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64478c7631
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Add Cohere2 model (#35224) | ||
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Pavel Iakubovskii
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5fcf6286bf
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Add TimmWrapper (#34564)
* Add files * Init * Add TimmWrapperModel * Fix up * Some fixes * Fix up * Remove old file * Sort out import orders * Fix some model loading * Compatible with pipeline and trainer * Fix up * Delete test_timm_model_1/config.json * Remove accidentally commited files * Delete src/transformers/models/modeling_timm_wrapper.py * Remove empty imports; fix transformations applied * Tidy up * Add image classifcation model to special cases * Create pretrained model; enable device_map='auto' * Enable most tests; fix init order * Sort imports * [run-slow] timm_wrapper * Pass num_classes into timm.create_model * Remove train transforms from image processor * Update timm creation with pretrained=False * Fix gamma/beta issue for timm models * Fixing gamma and beta renaming for timm models * Simplify config and model creation * Remove attn_implementation diff * Fixup * Docstrings * Fix warning msg text according to test case * Fix device_map auto * Set dtype and device for pixel_values in forward * Enable output hidden states * Enable tests for hidden_states and model parallel * Remove default scriptable arg * Refactor inner model * Update timm version * Fix _find_mismatched_keys function * Change inheritance for Classification model (fix weights loading with device_map) * Minor bugfix * Disable save pretrained for image processor * Rename hook method for loaded keys correction * Rename state dict keys on save, remove `timm_model` prefix, make checkpoint compatible with `timm` * Managing num_labels <-> num_classes attributes * Enable loading checkpoints in Trainer to resume training * Update error message for output_hidden_states * Add output hidden states test * Decouple base and classification models * Add more test cases * Add save-load-to-timm test * Fix test name * Fixup * Add do_pooling * Add test for do_pooling * Fix doc * Add tests for TimmWrapperModel * Add validation for `num_classes=0` in timm config + test for DINO checkpoint * Adjust atol for test * Fix docs * dev-ci * dev-ci * Add tests for image processor * Update docs * Update init to new format * Update docs in configuration * Fix some docs in image processor * Improve docs for modeling * fix for is_timm_checkpoint * Update code examples * Fix header * Fix typehint * Increase tolerance a bit * Fix Path * Fixing model parallel tests * Disable "parallel" tests * Add comment for metadata * Refactor AutoImageProcessor for timm wrapper loading * Remove custom test_model_outputs_equivalence * Add require_timm decorator * Fix comment * Make image processor work with older timm versions and tensor input * Save config instead of whole model in image processor tests * Add docstring for `image_processor_filename` * Sanitize kwargs for timm image processor * Fix doc style * Update check for tensor input * Update normalize * Remove _load_timm_model function --------- Co-authored-by: Amy Roberts <22614925+amyeroberts@users.noreply.github.com> |
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Aymeric Roucher
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9ad4c93536
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Add Aria (#34157)
* Add Aria --------- Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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João Marcelo
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50189e36a6
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Add I-JEPA (#33125)
* first draft * add IJepaEmbeddings class * fix copy-from for IJepa model * add weight conversion script * update attention class names in IJepa model * style changes * Add push_to_hub option to convert_ijepa_checkpoint function * add initial tests for I-JEPA * minor style changes to conversion script * make fixup related * rename conversion script * Add I-JEPA to sdpa docs * minor fixes * adjust conversion script * update conversion script * adjust sdpa docs * [run_slow] ijepa * [run-slow] ijepa * [run-slow] ijepa * [run-slow] ijepa * [run-slow] ijepa * [run-slow] ijepa * formatting issues * adjust modeling to modular code * add IJepaModel to objects to ignore in docstring checks * [run-slow] ijepa * fix formatting issues * add usage instruction snippet to docs * change pos encoding, add checkpoint for doc * add verify logits for all models * [run-slow] ijepa * update docs to include image feature extraction instructions * remove pooling layer from IJepaModel in image classification class * [run-slow] ijepa * remove pooling layer from IJepaModel constructor * update docs * [run-slow] ijepa * [run-slow] ijepa * small changes * [run-slow] ijepa * style adjustments * update copyright in init file * adjust modular ijepa * [run-slow] ijepa |
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Shane A
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9121ab8fe8
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Rename OLMo November to OLMo2 (#34864)
* Rename/move OLMo Nov files to OLMo2 * Rename Olmo1124 and its variants to Olmo2 |
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Shane A
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3ee24e2208
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Add OLMo November 2024 (#34551)
* Add model skeletion with transformers-cli add-new-model-like * Convert config to modular, add rms_norm_eps, delete clip_qkv * Convert model to modular, add RMSNorm * Add flash attention with qk norm and no qkv clipping * Add decoder layer with RMSNorm after attention/feedforward layers * Add base and causal model * Add converter improvements from OLMo repo * Update weight loading in OLMo to HF converter * Set correct default for rms_norm_eps * Set correct pipeline_model_mapping in test * Run make fixup * Fix model type * Re-run modular conversion * Manually set config docs to fix build errors * Convert olmo-1124 to olmo_1124 to fix flash attention docs errors * Start updating tests * Update tests * Copy upstream test_eager_matches_sdpa_inference_1_bfloat16 changes to olmo_1124 * Rename input_layernorm and post_attention_layernorm to reflect their ops better * Use correct tokenizer * Remove test unsupported by GPT2 tokenizer * Create GenerationConfig outside of from_pretrained call * Use simpler init file structure * Add explicit __all__ to support simplified init * Make safetensor serialization the default * Update OLMo November 2024 docs |
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Thomas Furtner
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30c76d5b28
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add code generation to natural language processing section (#34333) | ||
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Cyril Vallez
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6604764007
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add Glm (#33823)
* Create modular_glm.py * Update modular_glm.py * Finalize architecture without all attentions * Add all attentions modules * Finalize modular * Update given last version * Last update * Finalize model * Finalize converter * Update convert_glm_weights_to_hf.py * style * style * Create __init__.py * Aff all inits * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Correct the rotary embeddings * Remove apply_residual_connection_post_layernorm (always false) * remove use_rms_norm (always true) * remove past_layer_norm (always true) * Update __init__.py * Update config and license * start adding tests and doc * Add doc + style * Update test_modeling_glm.py * Add dummies * Apply correct modeling * Refactor attention to follow llama * Update __init__.py * Update convert_glm_weights_to_hf.py * Correct bias * remove linear_bias and pdrop (never used) * apply modular * Simplify converter * remove dummies + style * add model_input_names * Add pretraining_tp to config for when eager attention is used * Update modular to remove all pretraining_tp * Update test_modeling_glm.py * Update the __all__ * Update __all__ * Update __init__.py * Update test_modeling_glm.py * add revisions * Add the correct repos and revisions * style * Update __init__.py * update exports * remove import of modular files * style * Apply Llama changes + refine converter * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * Update convert_glm_weights_to_hf.py * style * Use new modular converter * add pretrainedmodel to init * style * Update test_modeling_glm.py * Move config outside modular to please CI about docstrings * Add dummies to please CI * Update glm.md * Update glm.md |
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Yoach Lacombe
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9ba021ea75
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Moshi integration (#33624)
* clean mimi commit * some nits suggestions from Arthur * make fixup * first moshi WIP * converting weights working + configuration + generation configuration * finalize converting script - still missing tokenizer and FE and processor * fix saving model w/o default config * working generation * use GenerationMixin instead of inheriting * add delay pattern mask * fix right order: moshi codes then user codes * unconditional inputs + generation config * get rid of MoshiGenerationConfig * blank user inputs * update convert script:fix conversion, add tokenizer, feature extractor and bf16 * add and correct Auto classes * update modeling code, configuration and tests * make fixup * fix some copies * WIP: add integration tests * add dummy objects * propose better readiblity and code organisation * update tokenization tests * update docstrigns, eval and modeling * add .md * make fixup * add MoshiForConditionalGeneration to ignore Auto * revert mimi changes * re * further fix * Update moshi.md * correct md formating * move prepare causal mask to class * fix copies * fix depth decoder causal * fix and correct some tests * make style and update .md * correct config checkpoitn * Update tests/models/moshi/test_tokenization_moshi.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update tests/models/moshi/test_tokenization_moshi.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * make style * Update src/transformers/models/moshi/__init__.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fixup * change firm in copyrights * udpate config with nested dict * replace einsum * make style * change split to True * add back splt=False * remove tests in convert * Update tests/models/moshi/test_modeling_moshi.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * add default config repo + add model to FA2 docstrings * remove logits float * fix some tokenization tests and ignore some others * make style tokenization tests * update modeling with sliding window + update modeling tests * [run-slow] moshi * remove prepare for generation frol CausalLM * isort * remove copied from * ignore offload tests * update causal mask and prepare 4D mask aligned with recent changes * further test refine + add back prepare_inputs_for_generation for depth decoder * correct conditional use of prepare mask * update slow integration tests * fix multi-device forward * remove previous solution to device_map * save_load is flaky * fix generate multi-devices * fix device * move tensor to int --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: Marc Sun <marc@huggingface.co> |
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pglorio
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f319ba16fa
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Add Zamba (#30950)
* Update index.md * Rebase * Rebase * Updates from make fixup * Update zamba.md * Batched inference * Update * Fix tests * Fix tests * Fix tests * Fix tests * Update docs/source/en/model_doc/zamba.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update docs/source/en/model_doc/zamba.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update configuration_zamba.py * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update modeling_zamba.py * Update modeling_zamba.py * Update modeling_zamba.py * Update configuration_zamba.py * Update modeling_zamba.py * Update modeling_zamba.py * Merge branch 'main' of https://github.com/Zyphra/transformers_zamba * Update ZambaForCausalLM * Update ZambaForCausalLM * Describe diffs with original mamba layer * Moved mamba init into `_init_weights` * Update index.md * Rebase * Rebase * Updates from make fixup * Update zamba.md * Batched inference * Update * Fix tests * Fix tests * Fix tests * Fix tests * Update docs/source/en/model_doc/zamba.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update docs/source/en/model_doc/zamba.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update configuration_zamba.py * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update modeling_zamba.py * Update modeling_zamba.py * Update modeling_zamba.py * Update configuration_zamba.py * Update modeling_zamba.py * Update modeling_zamba.py * Merge branch 'main' of https://github.com/Zyphra/transformers_zamba * Update ZambaForCausalLM * Moved mamba init into `_init_weights` * Update ZambaForCausalLM * Describe diffs with original mamba layer * make fixup fixes * quality test fixes * Fix Zamba model path * circleci fixes * circleci fixes * circleci fixes * circleci fixes * circleci fixes * circleci fixes * circleci fixes * circleci fixes * circleci fixes * Update * circleci fixes * fix zamba test from merge * fix ValueError for disabling mamba kernels * add HF copyright Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * shared_transf --> shared_transformer * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Fixes * Move attention head dim to config * Fix circle/ci tests * Update modeling_zamba.py * apply GenerationMixin inheritance change from upstream * apply import ordering * update needed transformers version for zamba Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * add contribution author * add @slow to avoid CI * Update src/transformers/models/zamba/modeling_zamba.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Define attention_hidden_size * Added doc for attention_head_size * trigger CI * Fix doc of attention_hidden_size * [run-slow] zamba * Fixed shared layer logic, swapped up<->gate in mlp * shared_transformer -> shared_transf * reformat HybridLayer __init__ * fix docstrings in zamba config * added definition of _get_input_ids_and_config * fixed formatting of _get_input_ids_and_config --------- Co-authored-by: root <root@node-4.us-southcentral1-a.compute.internal> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: root <root@node-1.us-southcentral1-a.compute.internal> Co-authored-by: Quentin Anthony <qganthony@yahoo.com> |
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Amit Garg
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e3775539c8
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PhiMoE (#33363)
* onboard phimoe model * removed debug code * added unit tests * updated docs * formatted * fixed unit tests * fixed test case * fixed format * refactored code * fixed expected outputs in the integration tests * Added a warning msg * Addressed comments * Addressed comments * fixed test cases * added paper link * Addressed comments * Refactored PhimoeForCausalLM forward fn * Refactored PhimoeRotaryEmbedding class * fixed test cases * fixed testcase * fixed test case * Addressed comments * fixed test cases * fixed testcases * Used cache position instead to get the seq len |
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Andrés Marafioti
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f2c388e3f9
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Add Idefics 3! (#32473)
* Add Idefics 3! * fixes to make both pipelines identical * fix for quantized models * First pass at the review * remove vocab size from the main config (it's still in the text_config) * hot fix for merve * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * re-add model_type for text_config * remove support for old_cache * remove hidden_size from main config * rename idefics3 HF repo * few changes suggested in the PR * fix to input_data_format computation * remove overwrite of _autoset_attn_implementation following @zucchini-nlp suggestion * improve example * few improvements from amy's review * big change to enable processing input images as numpy arrays * Changes to the code to uniformize processor kwargs * image processing tests * image processing tests fixes and some bugs they discovered * addressed review comments from Yoni * fix modeling tests * remove special tokens that are not special * fixes tests * skip failing tests - they also fail for idefics2 * added paper and readded the tests with multi gpu, who knows * Update docs/source/en/model_doc/idefics3.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * review amy until image_processing_idefics3 * last comments from Amy * review amy * Update src/transformers/models/idefics3/image_processing_idefics3.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/idefics3/modeling_idefics3.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/idefics3.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * doc improvement - amy review * fix runtime error during fine-tuning * amy's review * Update src/transformers/models/idefics3/image_processing_idefics3.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/idefics3/image_processing_idefics3.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/idefics3/modeling_idefics3.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * ruff * amy's comment on the order * ruff ruff * fix copies * square images when they are not splitted * ruff :( * Update src/transformers/models/idefics3/image_processing_idefics3.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/idefics3/test_processing_idefics3.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * fix small bug introduced in refactor * amy's image processing changes * fixes peft tests and ruff * modify to_pil_image from transformers. and review from emanuele. * add modified to_pil_image --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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Arthur
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19d58d31f1
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Add MLLama (#33703)
* current changes
* nit
* Add cross_attenttion_mask to processor
* multi-image fixed
* Add cross_attenttion_mask to processor
* cross attn works in all cases
* WIP refactoring function for image processor
* WIP refactoring image processor functions
* Refactor preprocess to use global loops instead of list nested list comps
* Docstrings
* Add channels unification
* fix dtype issues
* Update docsrings and format
* Consistent max_image_tiles
* current script
* updates
* Add convert to rgb
* Add image processor tests
* updates!
* update
* god damn it I am dumb sometimes
* Precompute aspect ratios
* now this works, full match
* fix 😉
* nits
* style
* fix model and conversion
* nit
* nit
* kinda works
* hack for sdpa non-contiguous bias
* nits here and there
* latest c hanges
* merge?
* run forward
* Add aspect_ratio_mask
* vision attention mask
* update script and config variable names
* nit
* nits
* be able to load
* style
* nits
* there
* nits
* make forward run
* small update
* enable generation multi-turn
* nit
* nit
* Clean up a bit for errors and typos
* A bit more constant fixes
* 90B keys and shapes match
* Fix for 11B model
* Fixup, remove debug part
* Docs
* Make max_aspect_ratio_id to be minimal
* Update image processing code to match new implementation
* Adjust conversion for final checkpoint state
* Change dim in repeat_interleave (accordig to meta code)
* tmp fix for num_tiles
* Fix for conversion (gate<->up, q/k_proj rope permute)
* nits
* codestyle
* Vision encoder fixes
* pass cross attn mask further
* Refactor aspect ratio mask
* Disable text-only generation
* Fix cross attention layers order, remove q/k norm rotation for cross atention layers
* Refactor gated position embeddings
* fix bugs but needs test with new weights
* rope scaling should be llama3
* Fix rope scaling name
* Remove debug for linear layer
* fix copies
* Make mask prepare private func
* Remove linear patch embed
* Make precomputed embeddings as nn.Embedding module
* MllamaPrecomputedAspectRatioEmbedding with config init
* Remove unused self.output_dim
* nit, intermediate layers
* Rename ln and pos_embed
* vision_chunk_size -> image_size
* return_intermediate -> intermediate_layers_indices
* vision_input_dim -> hidden_size
* Fix copied from statements
* fix most tests
* Fix more copied from
* layer_id->layer_idx
* Comment
* Fix tests for processor
* Copied from for _prepare_4d_causal_attention_mask_with_cache_position
* Style fix
* Add MllamaForCausalLM
* WIP fixing tests
* Remove duplicated layers
* Remove dummy file
* Fix style
* Fix consistency
* Fix some TODOs
* fix language_model instantiation, add docstring
* Move docstring, remove todos for precomputed embeds (we cannot init them properly)
* Add initial docstrings
* Fix
* fix some tests
* lets skip these
* nits, remove print, style
* Add one more copied from
* Improve test message
* Make validate func private
* Fix dummy objects
* Refactor `data_format` a bit + add comment
* typos/nits
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
* fix dummy objects and imports
* Add chat template config json
* remove num_kv_heads from vision attention
* fix
* move some commits and add more tests
* fix test
* Remove `update_key_name` from modeling utils
* remove num-kv-heads again
* some prelimiary docs
* Update chat template + tests
* nit, conversion script max_num_tiles from params
* Fix warning for text-only generation
* Update conversion script for instruct models
* Update chat template in converstion + test
* add tests for CausalLM model
* model_max_length, avoid null chat_template
* Refactor conversion script
* Fix forward
* Fix integration tests
* Refactor vision config + docs
* Fix default
* Refactor text config
* Doc fixes
* Remove unused args, fix docs example
* Squashed commit of the following:
commit b51ce5a2efffbecdefbf6fc92ee87372ec9d8830
Author: qubvel <qubvel@gmail.com>
Date: Wed Sep 18 13:39:15 2024 +0000
Move model + add output hidden states and output attentions
* Fix num_channels
* Add mllama text and mllama vision models
* Fixing repo consistency
* Style fix
* Fixing repo consistency
* Fixing unused config params
* Fix failed tests after refactoring
* hidden_activation -> hidden_act for text mlp
* Remove from_pretrained from sub-configs
* Apply suggestions from code review
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/mllama/convert_mllama_weights_to_hf.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Reuse lambda in conversion script
* Remove run.py
* Update docs/source/en/model_doc/mllama.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/mllama/processing_mllama.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Remove unused LlamaTokenizerFast
* Fix logging
* Refactor gating
* Remove cycle for collecting intermediate states
* Refactor text-only check, add integration test for text-only
* Revert from pretrained to configs
* Fix example
* Add auto `bos_token` adding in processor
* Fix tips
* Update src/transformers/models/auto/tokenization_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Enable supports_gradient_checkpointing model flag
* add eager/sdpa options
* don't skip attn tests and bring back GC skips (did i really remove those?)
* Fix signature, but get error with None gradient
* Fix output attention tests
* Disable GC back
* Change no split modules
* Fix dropout
* Style
* Add Mllama to sdpa list
* Add post init for vision model
* Refine config for MllamaForCausalLMModelTest and skipped tests for CausalLM model
* if skipped, say it, don't pass
* Clean vision tester config
* Doc for args
* Update tests/models/mllama/test_modeling_mllama.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Add cross_attention_mask to test
* typehint
* Remove todo
* Enable gradient checkpointing
* Docstring
* Style
* Fixing and skipping some tests for new cache
* Mark flaky test
* Skip `test_sdpa_can_compile_dynamic` test
* Fixing some offload tests
* Add direct GenerationMixin inheritance
* Remove unused code
* Add initializer_range to vision config
* update the test to make sure we show if split
* fix gc?
* Fix repo consistency
* Undo modeling utils debug changes
* Fix link
* mllama -> Mllama
* [mllama] -> [Mllama]
* Enable compile test for CausalLM model (text-only)
* Fix TextModel prefix
* Update doc
* Docs for forward, type hints, and vision model prefix
* make sure to reset
* fix init
* small script refactor and styling
* nit
* updates!
* some nits
* Interpolate embeddings for 560 size and update integration tests
* nit
* does not suppor static cache!
* update
* fix
* nit2
* this?
* Fix conversion
* Style
* 4x memory improvement with image cache AFAIK
* Token decorator for tests
* Skip failing tests
* update processor errors
* fix split issues
* style
* weird
* style
* fix failing tests
* update
* nit fixing the whisper tests
* fix path
* update
---------
Co-authored-by: raushan <raushan@huggingface.co>
Co-authored-by: pavel <ubuntu@ip-10-90-0-11.ec2.internal>
Co-authored-by: qubvel <qubvel@gmail.com>
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
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Yoni Gozlan
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94f18cf23c
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Add OmDet-Turbo (#31843)
* Add template with add-new-model-like * Add rough OmDetTurboEncoder and OmDetTurboDecoder * Add working OmDetTurbo convert to hf * Change OmDetTurbo encoder to RT-DETR encoder * Add swin timm backbone as default, add always partition fix for swin timm * Add labels and tasks caching * Fix make fix-copies * Format omdet_turbo * fix Tokenizer tests * Fix style and quality * Reformat omdet_turbo * Fix quality, style, copies * Standardize processor kwargs * Fix style * Add output_hidden_states and ouput_attentions * Add personalize multi-head attention, improve docstrings * Add integrated test and fix copy, style, quality * Fix unprotected import * Cleanup comments and fix unprotected imports * Add fix different prompts in batch (key_padding_mask) * Add key_padding_mask to custom multi-head attention module * Replace attention_mask by key_padding_mask * Remove OmDetTurboModel and refactor * Refactor processing of classes and abstract use of timm backbone * Add testing, fix output attentions and hidden states, add cache for anchors generation * Fix copies, style, quality * Add documentation, conver key_padding_mask to attention_mask * revert changes to backbone_utils * Fic docstrings rst * Fix unused argument in config * Fix image link documentation * Reorder config and cleanup * Add tokenizer_init_kwargs in merge_kwargs of the processor * Change AutoTokenizer to CLIPTokenizer in convert * Fix init_weights * Add ProcessorMixin tests, Fix convert while waiting on uniform kwargs * change processor kwargs and make task input optional * Fix omdet docs * Remove unnecessary tests for processor kwargs * Replace nested BatchEncoding output of the processor by a flattened BatchFeature * Make modifications from Pavel review * Add changes Amy review * Remove unused param * Remove normalize_before param, Modify processor call docstring * Remove redundant decoder class, add gradient checkpointing for decoder * Remove commented out code * Fix inference in fp16 and add fp16 integrated test * update omdet md doc * Add OmdetTurboModel * fix caching and nit * add OmDetTurboModel to tests * nit change repeated key test * Improve inference speed in eager mode * fix copies * Fix nit * remove OmdetTurboModel * [run-slow] omdet_turbo * [run-slow] omdet_turbo * skip dataparallel test * [run-slow] omdet_turbo * update weights to new path * remove unnecessary config in class --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-91-248.ec2.internal> |
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NielsRogge
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06e27e3dc0
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[Pixtral] Improve docs, rename model (#33491)
* Improve docs, rename model * Fix style * Update repo id |
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Mayank Mishra
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e472e077c2
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Granitemoe (#33207)
* first commit * drop tokenizer * drop tokenizer * drop tokenizer * drop convert * granite * drop tokenization test * mup * fix * reformat * reformat * reformat * fix docs * stop checking for checkpoint * update support * attention multiplier * update model * tiny drop * saibo drop * skip test * fix test * fix test * drop * drop useless imports * update docs * drop flash function * copied from * drop pretraining tp * drop pretraining tp * drop pretraining tp * drop unused import * drop code path * change name * softmax scale * head dim * drop legacy cache * rename params * cleanup * fix copies * comments * add back legacy cache * multipliers * multipliers * multipliers * text fix * fix copies * merge * multipliers * attention multiplier * drop unused imports * add granitemoe * add decoration * remove moe from sequenceclassification * fix test * fix * fix * fix * move rope? * merge * drop bias * drop bias * Update src/transformers/models/granite/configuration_granite.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix * Update src/transformers/models/granite/modeling_granite.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix * fix * fix * fix * drop * drop * fix * fix * cleanup * cleanup * fix * fix granite tests * fp32 test * fix * drop jitter * fix * rename * rename * fix config * add gen test --------- Co-authored-by: Yikang Shen <yikang.shn@gmail.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Yoach Lacombe
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5af7d41e49
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Codec integration (#33565)
* clean mimi commit * some nits suggestions from Arthur * make fixup * rename repo id + change readme * Update docs/source/en/model_doc/mimi.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * add flaky flag to batching equivalence due to audio_codes failing sometimes --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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Arthur
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8bd2b1e8c2
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Add support for Pixtral (#33449)
* initial commit * gloups * updates * work * weights match * nits * nits * updates to support the tokenizer :) * updates * Pixtral processor (#33454) * rough outline * Add in image break and end tokens * Fix * Udo some formatting changes * Set patch_size default * Fix * Fix token expansion * nit in conversion script * Fix image token list creation * done * add expected results * Process list of list of images (#33465) * updates * working image and processor * this is the expected format * some fixes * push current updated * working mult images! * add a small integration test * Uodate configuration docstring * Formatting * Config docstring fix * simplify model test * fixup modeling and etests * Return BatchMixFeature in image processor * fix some copies * update * nits * Update model docstring * Apply suggestions from code review * Fix up * updates * revert modeling changes * update * update * fix load safe * addd liscence * update * use pixel_values as required by the model * skip some tests and refactor * Add pixtral image processing tests (#33476) * Image processing tests * Add processing tests * woops * defaults reflect pixtral image processor * fixup post merge * images -> pixel values * oups sorry Mr docbuilder * isort * fix * fix processor tests * small fixes * nit * update * last nits * oups this was really breaking! * nits * is composition needs to be true --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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Raushan Turganbay
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43df47d8e7
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Llava Onevision: add model (#32673)
* working version * fix copies * update * tests * update docs * codestyle * add more tests * add returns for docs * clean up * Update src/transformers/models/llava_onevision/processing_llava_onevision.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * updates * codestyle * style * shouldn't be reversed * [run-slow] llava_onevision * [run-slow] llava_onevision * add pooling in videos * [run-slow] llava_onevision * num-logits-to-keep * [run-slow] llava_onevision * [run-slow] llava_onevision * Update tests/test_modeling_common.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * video matched orig impl * fix tests * chat template was modified * Update docs/source/en/model_doc/llava_onevision.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * add morer info in the doc page --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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Niklas Muennighoff
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ecd61c6286
|
Add OLMoE (#32406)
* Add OLMoE * Add OLMoE * Updates * Make norm optional; add keys * Add output * Add * Fix dtype * Fix eos config * Update * Add OLMoE * Fix OLMoE path * Format * Format * Rmv copy statement * Rmv copy statement * Format * Add copies * Cp rotary * Fix aming * Fix naming * Update RoPE integration; num_logits_to_keep; Add copy statements * Add eps to config * Format * Add aux loss * Adapt router_aux_loss_coef * Update md * Adapt * adapt tests |
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Mayank Mishra
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c35d2ccf5a
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Granite language models (#31502)
* first commit * drop tokenizer * drop tokenizer * drop tokenizer * drop convert * granite * drop tokenization test * mup * fix * reformat * reformat * reformat * fix docs * stop checking for checkpoint * update support * attention multiplier * update model * tiny drop * saibo drop * skip test * fix test * fix test * drop * drop useless imports * update docs * drop flash function * copied from * drop pretraining tp * drop pretraining tp * drop pretraining tp * drop unused import * drop code path * change name * softmax scale * head dim * drop legacy cache * rename params * cleanup * fix copies * comments * add back legacy cache * multipliers * multipliers * multipliers * text fix * fix copies * merge * multipliers * attention multiplier * drop unused imports * fix * fix * fix * move rope? * Update src/transformers/models/granite/configuration_granite.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix * Update src/transformers/models/granite/modeling_granite.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix * fix * fix * fix * fix-copies * torch rmsnorm * add authors * change model path * fix * test * drop static cache test * uupdate readme * drop non-causal * readme * drop useless imports * Update docs/source/en/model_doc/granite.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update docs/source/en/model_doc/granite.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update docs/source/en/model_doc/granite.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Shijie
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19e6e80e10
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support qwen2-vl (#32318)
* support-qwen2-vl * tidy * tidy * tidy * tidy * tidy * tidy * tidy * hyphen->underscore * make style * add-flash2-tipd * delete-tokenize=False * remove-image_processor-in-init-file * add-qwen2_vl-in-MODEL_FOR_VISION_2_SEQ_MAPPING_NAMES * format-doct * support-Qwen2VLVisionConfig * remove-standardize_cache_format * fix-letter-varaibles * remove-torch-in-image-processor * remove-useless-docstring * fix-one-letter-varaible-name * change-block-name * default-quick-gelu-in-vision * remove-useless-doc * use-preimplemented-flash-forward * fix-doc * fix-image-processing-doc * fix-apply-rotary-embed * fix-flash-attn-sliding-window * refactor * remove-default_template * remove-reorder_cache * simple-get-rope_deltas * update-prepare_inputs_for_generation * update-attention-mask * update-rotary_seq_len * remove-state * kv_seq_length * remove-warning * _supports_static_cache * remove-legacy-cache * refactor * fix-replace * mrope-section-doc * code-quality * code-quality * polish-doc * fix-image-processing-test * update readme * Update qwen2_vl.md * fix-test * Update qwen2_vl.md * nit * processor-kwargs * hard-code-norm_layer * code-quality * discard-pixel-values-in-gen * fix-inconsistent-error-msg * unify-image-video * hidden_act * add-docstring * vision-encode-as-PreTrainedModel * pixel-to-target-dtype * update doc and low memoryvit * format * format * channel-foramt * fix vit_flashatt * format * inherit-Qwen2VLPreTrainedModel * simplify * format-test * remove-one-line-func-in-image-processing * avoid-one-line-reshape * simplify-rotary_seq_len * avoid-single-letter-variable * no-for-loop-sdpa * avoid-single-letter-variable * remove-one-line-reshape * remove-one-line-reshape * remove-no-rope-in-vit-logic * default-mrope * add-copied-from * more-docs-for-mrope * polish-doc * comment-and-link * polish-doc * single-letter-variables * simplify-image-processing * video->images * kv_seq_len-update * vision-rope-on-the-fly * vision-eager-attention * change-processor-order --------- Co-authored-by: baishuai <baishuai.bs@alibaba-inc.com> Co-authored-by: ShuaiBai623 <43326198+ShuaiBai623@users.noreply.github.com> |
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Kamil Akesbi
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8260cb311e
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Add Descript-Audio-Codec model (#31494)
* dac model * original dac works * add dac model * dac can be instatiated * add forward pass * load weights * all weights are used * convert checkpoint script ready * test * add feature extractor * up * make style * apply cookicutter * fix tests * iterate on FeatureExtractor * nit * update dac doc * replace nn.Sequential with nn.ModuleList * nit * apply review suggestions 1/2 * Update src/transformers/models/dac/modeling_dac.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * up * apply review suggestions 2/2 * update padding in FeatureExtractor * apply review suggestions * iterate on design and tests * add integration tests * feature extractor tests * make style * all tests pass * make style * fixup * apply review suggestions * fix-copies * apply review suggestions * apply review suggestions * Update docs/source/en/model_doc/dac.md Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * Update docs/source/en/model_doc/dac.md Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * anticipate transfer weights to descript * up * make style * apply review suggestions * update slow test values * update slow tests * update test values * update with CI values * update with vorace values * update test with slice * make style --------- Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> |
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MAHIR DAIYAN
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843e5e20ca
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Add Flax Dinov2 (#31960)
* tfmsenv restored in main * installed flax * forward pass done and all tests passed * make fix-copies and cleaning the scripts * fixup attempt 1 * fixup attempt 2 * fixup third attempt * fixup attempt 4 * fixup attempt 5 * dinov2 doc fixed * FlaxDinov2Model + ForImageClassification added to OBJECTS_TO_IGNORE * external pos_encoding layer removed * fixup attempt 6 * fixed integration test values * fixup attempt 7 * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * comments removed * comment removed from the test * fixup * Update src/transformers/models/dinov2/modeling_flax_dinov2.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * new fixes 1 * interpolate_pos_encoding function removed * droppath rng fixed, pretrained beit copied-from still not working * modeling_flax_dinov2.py reformatted * Update tests/models/dinov2/test_modeling_flax_dinov2.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * added Copied from, to the tests * copied from statements removed from tests * fixed copied from statements in the tests * [run_slow] dinov2 --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> |
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Yangshen⚡Deng
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a27182b7fc
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Fix AutoConfig and AutoModel support for Llava-Next-Video (#32844)
* Fix: fix all model_type of Llava-Next-Video to llava_next_video * Fix doc for llava_next_video * * Fix formatting issues * Change llava-next-video.md file name into llava_next_video.md to make it compatible with implementation * Fix docs TOC for llava-next-video |
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Younes Belkada
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7c11491208
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Add new model (#32615)
* v1 - working version * fix * fix * fix * fix * rename to correct name * fix title * fixup * rename files * fix * add copied from on tests * rename to `FalconMamba` everywhere and fix bugs * fix quantization + accelerate * fix copies * add `torch.compile` support * fix tests * fix tests and add slow tests * copies on config * merge the latest changes * fix tests * add few lines about instruct * Apply suggestions from code review Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix * fix tests --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Yunfei Chu
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16ed0640be
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Add Qwen2-Audio (#32137)
* add qwen2audio * Update check_repo.py * fix style * fix test * fix style * add model size * Qwen2AudioEncoderModel->Qwen2AudioEncoder; add copy info * Update src/transformers/models/qwen2_audio/modeling_qwen2_audio.py Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * Update src/transformers/models/qwen2_audio/modeling_qwen2_audio.py Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * Update src/transformers/models/qwen2_audio/modeling_qwen2_audio.py Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * switch the attention_mask and the feature_attention_mask * add to PRIVATE_MODELS in check_repo.py; add to MODEL_NAMES_TO_IGNORE in check_table.py * fix initialization * update chat_template * fix consistency issue after copy * add docstrings to _merge_input_ids_with_audio_features * add copied from to prepare_inputs_for_generation * add more details to docs * rm comment * add init_std * Update src/transformers/models/qwen2_audio/modeling_qwen2_audio.py Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * Update src/transformers/models/qwen2_audio/modeling_qwen2_audio.py Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * Update src/transformers/models/qwen2_audio/modeling_qwen2_audio.py Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * Update src/transformers/models/qwen2_audio/modeling_qwen2_audio.py Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * update * Update docs/source/en/model_doc/qwen2_audio.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * update tests * rm ignore_index * update processor * rm ffmpeg_read * Update tests/models/qwen2_audio/test_modeling_qwen2_audio.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/qwen2_audio.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/qwen2_audio.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/qwen2_audio.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * update * typo * [run_slow] qwen2_audio * [run_slow] qwen2_audio * [run_slow] qwen2_audio * fix quality * [run_slow] qwen2_audio * [run_slow] qwen2_audio * [run_slow] qwen2_audio * add official model --------- Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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Pablo Montalvo
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80b90e7b2f
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Add codestral mamba2 (#32080)
* add new model like
* draft cuda forward - mismatched keys (sharding on conv1)
* match keys successfully
* fix split
* get generation/forward running (wrong gens, norm?)
* :update
* some refactoring
* fixes
* works up until copy to cache
* fix
* update
* NON WORKING VERSION
* version that work?
* nit
* fix config
* fix conversion script
* working cuda forward
* nit
* update
* simplifcation
* make mamba slow simple work
* no einops
* todo
* fix style
* no einops
* update fix no einsum
* nit
* remove einops
* bug: scan_output differs strongly
* add rms norm option
* fix fast + slow generation with and w/o cache ✔️
* draft integration tests
* remove a big chunk of the einsum
* fix slow, fast generations, without any einsum
* fix copies
* fix structure
* fix up modeling and tests
* fix tests
* clamping is indeed worse
* recover mamba2 cache test
* fix copies
* no cache position (yet)
* fix tf tests
* fix matmul for generate
* fixup
* skip cache tests for now
* [run-slow]mamba2
* tune out hidden states for padding
* test batched generation
* propagate attention mask changes
* fix past length
* fix integration test
* style
* address comments
* update readme
* add mamba2 version check
* fix tests
* [run-slow]mamba2
* skip edge tests
* [run-slow]mamba2
* last fixup
* [run-slow]mamba2
* update README
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
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Ao Tang
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6a03942db7
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Add Nemotron HF Support (#31699)
* Add nemotron support * fix inference * add unit test * add layernorm1p as a class to avoid meta device mismatch * test fixed * Add copied_from statements * remove pretraining_tp args * remove nemotronlayernorm * force LN computation done in FP32 * remove nemotrontokenizer and use llamatokenizer * license update * add option for kv_channels for minitron8b * remove assert * o_proj fixed * o_proj reshape * add gated_proj option * typo * remove todos * fix broken test after merging latest main * remove nezha/nat after meging main * chnage default config to 15b model * add nemo conversion script * rename conversion script * remove gate_proj option * pr comment resolved * fix unit test * rename kv_channels to head_dim * resolve PR issue * add nemotron md * fix broken tests * refactor rope for nemotron * test fix * remove linearscaling * whitespace and import * fix some copied-from * code style fix * reformatted * add position_embedding to nemotronattention * rope refactor to only use config, copied-from fix * format * Run make fix-copies * nemotron md with autodoc * doc fix * fix order * pass check_config_docstrings.py * fix config_attributes * remove all llama BC related code * Use PreTrainedTokenizerFast * ruff check examples * conversion script update * add nemotron to toctree |
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Raushan Turganbay
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24cfcc2114
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Chameleon: add model (#31534)
* Chameleon model integration Co-authored-by: Jacob Kahn <jacobkahn1@gmail.com> Co-authored-by: Leonid Shamis <leonid.shamis@gmail.com> * fix 7B, again. mask away image tokens * Apply suggestions from code review Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * remove pretrained_config_map * make fixup passing up to utils/check_config_docstrings.py; vqgan moved to the modeling file * remove tokenizer (use llama's); remove codechameleon tests * a few copied from statements and minor changes * copied from in ChameleonModel * some copies in ChameleonForCausalLM * a few more copies * VQModel moved to ChameleonModel (as opposed to being in the processor) * ChameleonProcessor ready * Fix chameleon weights convert * update conversion script * clean-up processing * update modeling a bit * update * update (throws error...) * correct conversion ready * fix tests * fix docs * docs * ve swin norm * fix device for vocab map * add normalization * update * update script with rope rotations * final fix on model conversion * add slow tests * more info in docs * fix repo consistency tests * fix repo tests * fix-copies * hope this will make CI happy * fix for 30b model * Update docs/source/en/index.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/chameleon.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/chameleon/modeling_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/chameleon.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/chameleon.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/chameleon.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/chameleon.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/auto/configuration_auto.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/chameleon/image_processing_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/chameleon/image_processing_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/chameleon/image_processing_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/chameleon/image_processing_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/chameleon/modeling_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/chameleon/processing_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/chameleon/processing_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/chameleon/test_modeling_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/chameleon/test_modeling_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/chameleon/test_modeling_chameleon.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * address comments * remove assertion in conversion script * add image processor test * not copied * port changes for qk layernorm * fix-copies * read token decorator for tests * [run-slow] chameleon * one more read-token * address some comments * qk norm changes * tests and repo check * moved rope permutations to conversion, YAY! * fix past kv check * docs * layernorm done! * let's be consistent in naming * fix slow tests * weird thing with slow CI, but let's see * once more try * remove past-kv as tuple following llama * ignore * style --------- Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com> Co-authored-by: ArthurZucker <arthur.zucker@gmail.com> Co-authored-by: jacobkahn <jacobkahn1@gmail.com> Co-authored-by: Leonid Shamis <leonid.shamis@gmail.com> Co-authored-by: Leonid Shamis <lshamis@meta.com> Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: Joao Gante <joao@huggingface.co> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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Naman Garg
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c1e139c2b0
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Adding hiera (#30356)
* initialized Structure * Updated variable names * Added Config class, basic HF setup, convert_to_hf * Fixed Convert function, added hiera to HF files, Initilized test files * better naming for x in forward pass * Moved utils to hiera * Change hiera -> hiera_model * Fixed integration into tranformers * Fix: Convert Checkpoint * added documentation for hiera * added documentation for hiera * added Docstings to models, Transformers based changes * make style and quality * make style and quality * Integration & Block tests running * Fixed bugs * initialized Structure * Updated variable names * Added Config class, basic HF setup, convert_to_hf * Fixed Convert function, added hiera to HF files, Initilized test files * better naming for x in forward pass * Moved utils to hiera * Change hiera -> hiera_model * Fixed integration into tranformers * Fix: Convert Checkpoint * added documentation for hiera * added documentation for hiera * added Docstings to models, Transformers based changes * make style and quality * make style and quality * Integration & Block tests running * Fixed bugs * Removed tim dependency * added HieraBlock * fixed: Model name * added tests for HieraModel, HieraBlock * fixed imports * fixed quality & copies * Fixes * Update docs/source/en/model_doc/hiera.md Fix name Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/hiera.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/hiera.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update src/transformers/models/hiera/configuration_hiera.py Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update src/transformers/models/hiera/configuration_hiera.py Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update src/transformers/models/hiera/modeling_hiera.py Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update src/transformers/models/hiera/modeling_hiera.py Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Fixed formatting * Code quality & Import differences * quality and repo-consistency fix * fixed no torch error * Docstring fix * Docstring fix * doc string fix * fixed example usage * Resolved issues in modeling_hiera * Removed Hiera MAE * Added test and resolved bug * fixed doc string * First commit * Finished conversion script and model forward working * Resolved all issues * nits * Improving tests * Nits * More nits * Improving HieraForMaskedImageModeling * More improvements and nits * Fixed docstrings of outputs * More fixes * More imrpovments * Updated conversion script * Fixed docstrings * Improved tests * Fixed attentou outputs test * All tests green * Removed unnecessary file * contribution attribution * Resolved a few issues * Resolved Comments * Updated model repo id and fixed bugs * Removed loss print * Make tests green * Updated docstrings * Fix style * Fixed num_heads in config * Removed unnecessary video checkpoint related code in the conversion script * Fix style * Changed atol in conversion script * HieraConfig * Fix copies * Fixed typo * Resolved few issues * make * converted conv_nd -> nn.Module * Removed video complexities * Removed video complexities * fix style * Addressing comments * Update src/transformers/models/hiera/modeling_hiera.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/hiera/modeling_hiera.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/hiera/modeling_hiera.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Fix style * Fixed tests * Fixed typo * Fixed interpolate test * Made torch fx compatible * Made sure imageprocesor is correct * Addressed comments * Noise directly as torch * Remove unnecesary attr * Added return_dit * Update src/transformers/models/hiera/__init__.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Updated checkpoints * [run_slow] hiera * Fixed device mismatch * [run_slow] hiera * Fixed GPU tests * [run_slow] hiera --------- Co-authored-by: Ubuntu <ubuntu@ip-172-31-29-50.us-east-2.compute.internal> Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by: Eduardo Pacheco <eduardo.pach@hotmail.com> Co-authored-by: Eduardo Pacheco <69953243+EduardoPach@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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NielsRogge
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06fd7972ac
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Add ZoeDepth (#30136)
* First draft * Add docs * Clean up code * Convert model * Add image processor * Convert Zoe_K * More improvements * Improve variable names and docstrings * Improve variable names * Improve variable names * Replace nn.sequential * More improvements * Convert ZoeD_NK * Fix most tests * Verify pixel values * Verify pixel values * Add squeeze * Update beit to support arbitrary window sizes * Improve image processor * Improve docstring * Improve beit * Improve model outputs * Add figure * Fix beit * Update checkpoint * Fix repo id * Add _keys_to_ignore_on_load_unexpected * More improvements * Address comments * Address comments * Address comments * Address comments * Rename variable name * Add backbone_hidden_size * Vectorize * Vectorize more * Address comments * Clarify docstring * Remove backbone_hidden_size * Fix image processor * Remove print statements * Remove print statement * Add integration test * Address comments * Address comments * Address comments * Address comments * Add requires_backends * Clean up * Simplify conversion script * Simplify more * Simplify more * Simplify more * Clean up * Make sure beit is loaded correctly * Address comment * Address bin_configurations * Use bin_configurations * Convert models, add integration tests * Fix doc test * Address comments * Unify regressor classes * Clarify arguments * Improve resize_image * Add num_relative_features * Address comment * [run-slow]beit,data2vec,zoedepth * [run-slow]beit,data2vec,zoedepth * Address comments * Address comment * Address comment * Replace nn.TransformerEncoderLayer and nn.TransformerEncoder * Replace nn.MultiheadAttention * Add attributes for patch transformer to config * Add tests for ensure_multiple_of * Update organization * Add tests * [run-slow] beit data2vec * Update ruff * [run-slow] beit data2vec * Add comment * Improve docstrings, add test * Fix interpolate_pos_encoding * Fix slow tests * Add docstring * Update src/transformers/models/zoedepth/image_processing_zoedepth.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/zoedepth/image_processing_zoedepth.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Improve tests and docstrings * Use run_common_tests * Improve docstrings * Improve docstrings * Improve tests * Improve tests * Remove print statements --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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Arthur
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0cf60f13ab
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Add gemma 2 (#31659)
* inital commit * Add doc * protect? * fixup stuffs * update tests * fix build documentation * mmmmmmm config attributes * style * nit * uodate * nit * Fix docs * protect some stuff --------- Co-authored-by: Lysandre <lysandre@huggingface.co> |
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Raushan Turganbay
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e71f2863d7
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Add LLaVa NeXT Video (#31252)
* squash into single commit * run diff once more * docstring * tests * minor chnages and ready to go * Update src/transformers/models/llava_next_video/processing_llava_next_video.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/vipllava/test_modeling_vipllava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * [run-slow] llava-next-video * [run-slow] llava-next-video * [run-slow] llava_next_video * fix two tests * fix slow tests * remove logit checks due to numeric errors * run test once more * [run-slow] llava_next_video * final try to pass the test * [run-slow] llava_next_video * [run-slow] llava_next_video * [run-slow] llava_next_video * style * fix * style --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> |
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Raushan Turganbay
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fc689d75a0
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Add video modality for InstrucBLIP (#30182)
* squash in single commit * add docs * dummy obj * more changes in diff converter * tiny fix * make docs happy * skip test * repo consistency tests * update docstring * style * fix tests * change diff imports * [run-slow] instructblipvideo * [run-slow] instructblipvideo * fix tests and remove logit check * [run-slow] instructblipvideo |
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Sangbum Daniel Choi
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74a207404e
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New model support RTDETR (#29077)
* fill out docs string in configuration |
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Aritra Roy Gosthipaty
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965e98dc54
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[Port] TensorFlow implementation of Mistral (#29708)
* chore: initial commit * chore: adding imports and inits * chore: adding the causal and classification code * chore: adding names to the layers * chore: using single self attn layer * chore: built the model and layers * chore: start with testing * chore: docstring change, transpose fix * fix: rotary embedding * chore: adding cache implementation * remove unused torch * chore: fixing the indexing issue * make fix-copies * Use modeling_tf_utils.keras * make fixup * chore: fixing tests * chore: adding past key value logic * chore: adding multi label classfication test * fix: switching on the built parameters in the layers * fixing repo consistency * ruff formats * style changes * fix: tf and pt equivalence * removing returns from docstrings * fix docstrings * fix docstrings * removing todos * fix copies * fix docstring * fix docstring * chore: using easier rotate_half * adding integration tests * chore: addressing review related to rotary embedding layer * review changes * [run-slow] mistral * skip: test save load after resize token embedding * style --------- Co-authored-by: Matt <rocketknight1@gmail.com> |
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Raushan Turganbay
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bd9f4d7951
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Add Video Llava (#29733)
* add model draft * update docstring * add tests * support image and video as input * update for better handling of mixed input and clean-up a bit * bug when mixed inputs & add tests * Update README.md Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Merge remote-tracking branch 'upstream/main' into video_llava * link to abstract of paper in README * fix test * fix-copies * make tests happy * skip docstest for now * do not run doctest for now * Update src/transformers/models/video_llava/processing_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/image_processing_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/image_processing_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/image_processing_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/image_processing_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/video_llava/test_modeling_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/image_processing_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * address review comments * failing tests * Fix vocab_size in common tests for VLMs * codestyle * Update src/transformers/models/video_llava/configuration_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/configuration_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/modeling_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/modeling_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/video_llava.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/video_llava.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/image_processing_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/video_llava.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/processing_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/video_llava/test_modeling_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/video_llava/test_modeling_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/video_llava/test_modeling_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * PR suggestions * fix-copies * Update src/transformers/models/video_llava/configuration_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/video_llava/configuration_video_llava.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * add full example in docs * clean-up with new model-id * [run-slow] video_llava * update docstring * [run-slow] video_llava * remove all achive maps * fix some tests * test was supposed to be skipped for llava :) --------- Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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Pablo Montalvo
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1360801a69
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Add PaliGemma (#30814)
* add new model like * add state dict slicing + new model config * update palma config and weights, passes vision activations * fix * update * reorder loading/unpacking * clean up * add debug statements * change device * fix * debugging * fix noncausal mask * fixup sdpa + causal mask * fix activation function * remove debug before changing modeling file * add variants * debug attention mask in generate * revert to non-debug sdpa * revert gemma modifications * add custom language modeling * use Processor * add language modeling file to init * try thin wrapper around generate * Update * update mask * breakpoints galore * remove conflict * switch to left-padding * add incomplete model doc * add paligemma global files * batch rename paligemma * make generation match outputs and captioning * style * style * remove copied from + doc * remove more copied from * remove copy from projector * minor fix * update config and style * add readme - dummy * CORRECT image captioning * moving to args * add siglip proper + fix merging image + text features * take update_causal_mask from upstream * remove breakpoint * leverage AutoModel * fix input_ids slicing * make siglip head conditional * remove encoder_decoder value * remove unneeded modeling file * add commented 4d attention mask * FIXED generation with 4D mask * Update src/transformers/models/siglip/modeling_siglip.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix left padding detection * shuffle order of verifications * fix missing labels for training * fix * vectorize merging of features, improve slicing * improve testing before conversion * handle merging in processor * image token index depends on checkpoint * add variants, save processor too * save processors, base tokenizer off spm file * expand model embeddings due to additional image token * pass image processing args * add convert rgb to siglip processor * add \n token separately * fix tokenizer and prompts * fix docstrings * change to camel * fix casing * debug pos_ids and sdpa * pass and use cache_position * add flag for newline tokenization * Update src/transformers/models/paligemma/processing_paligemma.py Co-authored-by: Merve Noyan <merveenoyan@gmail.com> * simplify conversion script * add copied from * add precision to conversion script * Update src/transformers/models/paligemma/modeling_paligemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * clean up * Shift attention mask from `1:` After discussion with @molbap * add docs, fix quality * quality, tied weights inheritance, and logits/label alignment * fix more tests * pass attn_implementation to language model correctly * add SiglipVisionTransformer to no split modules * skip paligemma test for sdpa dispatch to flash * skip incompatible tests * quality * [broken archive maps] * Apply suggestions - remove archive lists - style - take shape of inputs_embeds for batch Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/utils/dummy_pt_objects.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * simplify conversion script * add suggestions * add suggestions * add copied from * fix * move labels out * revert * fix * remove placeholder labels if None * use cache_position * fix quality + docstrings * fix quality * fix paligemma 4d gemma mask incompatibility * fix config docstring * fix query and attn_mask dtype --------- Co-authored-by: ArthurZucker <arthur.zucker@gmail.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: Merve Noyan <merveenoyan@gmail.com> Co-authored-by: Pedro Cuenca <pedro@huggingface.co> |
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Yikang Shen
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ccdabc5642
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Add JetMoE model (#30005)
* init jetmoe code * update archive maps * remove flax import * fix import error * update README * ruff fix * update readme * fix * update config * fix issue * merge files * fix model bug * fix test * auto fix * model size * add comments * fix form * add flash attention support * fix attention head number * fix init * fix support list * sort auto mapping * fix test * fix docs * update test * fix test * fix test * change variable name * fix config * fix init * update format * clean code * fix config * fix config * change default config * update config * fix issues * update formate * update config argument * update format * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * change to mixtral aux loss * change to cache_position * debug * fix bugs * debug * fix format * fix format * fix copy * fix format * fix format * fix sort * fix sort * fix sort * add copy comment * add copy from * remove debug code * revert readme update * add copy * debug * remove debug code * fix flash attention * add comments * clean code * clean format * fix format * fix format * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * change variable name * add copied from * fix variable name * remove deprecated functinos * sync to llama implementation * fix format * fix copy * fix format * update format * remove repr * add comment for moe weight * fix copy * Update src/transformers/models/jetmoe/configuration_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * add comments and reformat config * fix format * fix format * fix format * update test * update doc string in config * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * update config doc * update attention cache * fix format * fix copy --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> |
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Alazar
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94306352f4
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Port IDEFICS to tensorflow (#26870)
* Initial commit * Just a copy of modeling_idefics.py that will be ported to TF * - Prepend TF to the name of all classes - Convert pytorch ops to TF (not all operations are converted yet) * Add TF imports * Add autotranslated files * Add TF classes to model_tf_auto.py * Add the TF classes in model_doc * include auto-translated code * Adopted from auto-translated version * Add a forgotten super().build * Add test code for TF version. * Fix indentation and load pytorch weights for now * Some fixes. Many tests are still failing but some are passing now. - I have added TODO's for some of the hacks I made to unblock me and I will address them soon - I have the processing_idefics.py hacked in my view to support TF temporarily * Add ALL_LAYERNORM_LAYERS to match pytorch * Revert "Add ALL_LAYERNORM_LAYERS to match pytorch" This reverts commit 7e0a35119b4d7a6284d04d8c543fba1b29e573c9 as it is not needed in the tf implementation. * Fix freeze_relevant_params() * Some more fixes * Fix test_attention_outputs * Add tf stuff to processing_idefics.py processing_idefics.py supports both pytorch and tf now. test_processor_idefics.py for pytorch is passing, so i didn't break anything but still some issues with tf. I also need to add tf tests in test_processor_idefics.py. * Pass return_tensors to image processing code and fix test * Pass return_tensors to the image processor __init__ * Fix several test cases - Make input to some of the forward pass of type `TFModelInputType` - Decorate main layer forward pass with `@unpack_inputs` - Decorate main layer with `@keras_serializable` - Pass `inputs` to TFIdeficsModel * Some more fixes forgotten in last commit * Fix processing code and vision_tf.py * Fix perceiver bug * Import from * Auto-add build() methods + style pass * Fix build() errors due to `None` being passed as shape to some layers * Change name in TFIdeficsForVisionText2Text to attribute in IdeficsForVisionText2Text * Fix pytorch weights load for tf2 There were a lot of `name=` missing in weight initialization code. * Attempt to fix CI * Add back accidently removed line * Remove torch-specific stuff from the TF test file * make fix-copies, make style, remove autotranslated files * Fixes to imports/docstrings * Let's try the from future import in desperation * Fix the core random_attention_mask fn to match the torch/flax behaviour * Clean random_attention_mask up correctly * Remove torch-only test * Fix loss shape, couple of nits * make style * Don't test for OOB embeddings because IDEFICS uses those deliberately * Fix loss computation to handle masking * Fix test failures when flattening * Fix some test failures - Add cross attention gate which was missing and wasn't being passed arround - Fix overwriting of image_attention_mask due to hack I had for dummy inputs * Add a proper stateless scaled_dot_product_attention * make style * Adding missing attribute from the PyTorch version * Small cleanups to decoupledlinearlayer in case that helps * Pass epsilon to LayerNormalization * Attemp to fix pytorch weight cross-loading for TFIdeficsEmbedding * Fix a bug in TFIdeficsGatedCrossAttentionLayer * Patching up build() methods * Constant self.inv_freq * Constant self.inv_freq * First working version The TF implementation works now, there was a bug in the TFIdeficsDecoupledLinear where the weights were mis-intialized (in_features,out_features) when it should be: (out_features, in_features) I have tested this so far with tiny-random and idefics-9b-instruct and gives correct output. I also dumped the final outputs for both pytorch and TF and they are identical. * Fix some test failures * remove print statement * Fix return_tensors * Fix CI test failure check_code_quality * Attempt to fix CI failures by running `make fixup` The hardcoded IDs in test_modeling_tf_idefics.py are for the integration test and makes that file unreadable and should probably be moved to a seperate file. * Attempt to fix tests_pr_documentation_tests * Fix a test failure in test_image_processing_idefics.py * Fix test test_pt_tf_model_equivalence * Fix a few failures * Tiny fix * Some minor fixes * Remove a duplicate test * Override a few test failures for IDEFICS - `test_keras_save_load` is passing now - `test_compile_tf_model` is still failing * Fix processing_idefics.py after rebase * Guard import keras with is_tf_available * fix check code quality * fix check code quality * Minor fixes * Skip test_save_load temporarily This test passed on my local box but fails on the CI, skipping for now to see if there are other remaining failures on the CI. * Run `ruff format tests src utils` * Fix last failing test, `test_compile_tf_model` * Add fixes for vision_tf.py I forgot to add this file in last commit. * Minor fixes * Replace "<<<" with "<<" for doc tests IDEFICS-9B is too big for doctest runner, so don't run it there * Make code more readable * Fix bug after code review I added a layer_norm_eps to IdeficsConfig but I don't even need it since the vision config has a layer_norm_eps. * Fix after code review Use original code tokenizer.convert_tokens_to_ids * Keep PyTorch as the default return_tensors * Fixes to modeling_tf after code review * Fixes from code review - Remove all references of `TF_IDEFICS_PRETRAINED_MODEL_ARCHIVE_LIST` - Pass 1e-5 to LayerNormalization in perceiver * Run ruff * Undo a change * Refactor processing code after Matt's suggestion * Remove TODO's that aren't needed anymore * For pytorch, Use original pytorch processing code from main Since this PR is a TF port it shouldn't make any modifications to pytorch IDEFICS code. This changes undo's the pytorch processing modifications I made and uses original code from main. * Update tests/models/idefics/test_modeling_idefics.py * Update tests/models/idefics/test_modeling_tf_idefics.py * Add missing imports for is_pt_tf_cross_test * [DO NOT MERGE]: This is a commit for debugging and will be reverted The cross test `test_pt_tf_model_equivalence` passes locally but fails when running on the CI. This commit is to help debug that and will be reverted. * Revert "[DO NOT MERGE]: This is a commit for debugging and will be reverted" This reverts commit 8f0d709ec5bd46685fb0b4259d914ffee794875b. * [DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted * [DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted * Revert "[DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted" This reverts commit 998cc38b8c3d313bf5e5eb55a7f5b7b881897b89. * Revert "[DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted" This reverts commit 1c695ac4219c4ae4d39b330b01744dc27deb7dd4. * Don't skip test_save_load IIRC test_save_load was also failing on the CI but not on my local box, it might be easier to debug that on the CI first than the cross tests * Debugging commit, will be reverted * Revert "Debugging commit, will be reverted" This reverts commit 8eafc8e41e20c4e95a3a90834f06a6e9f445e2d5. * Override `test_save_load` and push model to save Maybe this will help me repro this weird bug * pass my repo_id * add endpoint * Pass a temp (write) token just for this CI * Undo last few commits, still pushing to hub for model debugging The issue seems to be with save_pretrained(), when I looked at the model saved from the CI test failure it is basically empty and has no weights. `self.save_weights(..)` seems to be failing in save_pretrained but needs more debugging * Add logging to modeling tf utils, will be reverted just for debugging * Debugging, will revert * Revert "Debugging, will revert" This reverts commit 9d0d3075fb7c82d8cde3a5c76bc8f3876c5c55d3. * Revert "Add logging to modeling tf utils, will be reverted just for debugging" This reverts commit 774b6b7b1c17b3ce5d7634ade768f2f686cee617. * Remove `test_save_load` The CI failures are gone after my latest rebase, no idea why but I was still saving the model to my hub on HF and the tf_model.h5 file now has everything. * Run make fix-copies * Run ruff format tests src utils * Debugging commit, will be reverted * Run ruff, also trigger CI run * Run ruff again * Undo debugging commit --------- Co-authored-by: Matt <rocketknight1@gmail.com> Co-authored-by: Matt <Rocketknight1@users.noreply.github.com> |
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Gustavo de Rosa
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c9693db2fc
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Phi-3 (#30423)
* chore(root): Initial commit of Phi-3 files. * fix(root): Fixes Phi-3 missing on readme. * fix(root): Ensures files are consistent. * fix(phi3): Fixes unit tests. * fix(tests): Fixes style of phi-3 test file. * chore(tests): Adds integration tests for Phi-3. * fix(phi3): Removes additional flash-attention usage, .e.g, swiglu and rmsnorm. * fix(phi3): Fixes incorrect docstrings. * fix(phi3): Fixes docstring typos. * fix(phi3): Adds support for Su and Yarn embeddings. * fix(phi3): Improves according first batch of reviews. * fix(phi3): Uses up_states instead of y in Phi3MLP. * fix(phi3): Uses gemma rotary embedding to support torch.compile. * fix(phi3): Improves how rotary embedding classes are defined. * fix(phi3): Fixes inv_freq not being re-computed for extended RoPE. * fix(phi3): Adds last suggestions to modeling file. * fix(phi3): Splits inv_freq calculation in two lines. |
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Arthur
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89c510d842
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Add llama3 (#30334)
* nuke * add co-author * add co-author * update card * fixup and fix copies to please our ci * nit fixup * super small nits * remove tokenizer_path from call to `write_model` * always safe serialize by default --------- Co-authored-by: pcuenca <pcuenca@users.noreply.github.com> Co-authored-by: xenova <xenova@users.noreply.github.com> |