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351 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Huajie Tan
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6f7ea1cf00
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Add MLCD model (#36182)
* Add MLCD model * Update codes for auto-mapping * Add test scripts for MLCD * Update doc for MLCD model * Fix import error * Fix import error * Fix CI error for attention_outputs * Fix code style for CI * Fix code style for CI * Fix code style for CI * Fix code style for CI * Fix code style for CI * Fix CI error for initialization * Fix code style for CI * Fix code style for CI * Reformat codes and docs for CI test * Reformat codes and docs for CI test * Remove unused attributes for CI test * Fix style for CI test * List MLCD in flash_attn doc * Fix: typos, modulars, refactors from suggestions * Refactoring convert_mlcd_weights_to_hf.py from suggestions * Fix: docs conflicts * Fix error for CI test * Fix style for CI test * Add integration test for MLCD * Refactoring by class inheritance * Fix: refactor attention interface, adjust codes * Fix: merging conflicts * Fix: merging conflicts * Fix: style for CI test * Fix: style for CI test * Fix: set test_resize_embeddings to be False * Fix: initializer for CI test * Fix: conflicts, CI test, warning and refactoring * Fix: merging conflicts * Refactor * Update docs * Fix mistakes * Remove unused args and fix multi-gpu error * Revert position_embeddings * Solve conflicts * Solve conflicts * Remove dummy * Update _init_weights * Update _init_weights * Update _init_weights for CI test |
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BakerBunker
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4b8c6d4cf8
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Add Qwen2.5-Omni (#36752)
* Add qwen2.5-omni * Remove einops dependency * Add torchdiffeq dependency * Sort init * Add torchdiffeq to extras['diffeq'] * Fix repo consistency * use cached_file * del odeint * renew pytest * format * Remove torchdiffeq * format * fixed batch infer bug * Change positional_embedding to parameter * Change default speaker * Config revision * Use modular & code clean * code clean * decouple padding with model & code cleaning * sort init * fix * fix * Second code review * fix * fix * rename vars to full name + some comments * update pytest * Code clean & fix * fix * style * more clean up * fixup * smaller vision model in tests * fix processor test * deflake a bit the tests (still flaky though) * de-flake tests finally + add generation mixin * final nits i hope * make sure processor tests are complete * replace with Qwen2_5OmniForConditionalGeneration * fix tests after updating ckpt * fix typos when cleaning, also we can't change ckpt * fixup * images and videos kwargs for processor * thinker and talker loadable from hub ckpt * address comments and update tests after rebase * fixup * skip for now * fixup * fixup * remove torch dependency in processors --------- Co-authored-by: lvyuanjun.lyj <lvyuanjun.lyj@alibaba-inc.con> Co-authored-by: feizi.wx <feizi.wx@alibaba-inc.com> Co-authored-by: raushan <raushan@huggingface.co> |
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Joao Gante
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aaf129cdae
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[agents] remove agents 🧹 (#37368) | ||
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Alex Brooks
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623d395aff
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Add Granite Speech Support (#36801)
* First pass at speech granite Add encoder / projector, rename things * Combine into one model file with causal lm outputs for forward * Add loss calc * Fix config loading Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com> * Split new / old loading logic * Use transformers integration for loading peft adapters * Add generation wrapper for selective lora enablement * Add note for qformer encoder automodel * Guard torch/audio imports in feature extractor * Handle granite speech autoclasses * Handle optional deps in package structure for granite speech * Add granite pretrained model def for init * Add dummy objects for torch/torchaudio * Add tests for granite speech processor * Minor formatting fixes and refactoring * Add options for falling back to config in forward * Tentative model docstrings for granite speech * Fix config type * Remove legacy load * Allow non-lora variants for granite speech * Override weight tying for llm * Use text config instead of llm config * Add output embeddings getter to fix weight tying * Fix relative imports * computing the number of audio features, based on the raw audio sequence. * collating audio inputs, and keeping the original lengths. * asserted we have text. otherwise we can't specify the audio special token. * assering the number of audio-symbols/audios match correctly. running get validated_audios only when audio is present * indentation bugfix + supporting different feature lengths when expanding audio. * redundant, done in _get_validated_text * adapting the tests: - we must have text (not either audio or text) - _get_num_audio_features takes a list of raw lengths, provided it insetad. * Minor cleanup, remove unused import * Add more tests for batch feature processing * Allow setting offset in rel position embeddings * Add config option for warning if peft is not installed w/ lora * Port blip2 qformer code into granite speech * Add sad test for numpy arr processing * Allow numpy arrays / tuples in granite speech processor * Fix config type for projector * - pad instead of creating a zeros tensor, to keep the original dtype/device (support bfloat16) - cast input_features to the model dtype (support bfloat16) * merge Blip2QFormerConfig to GraniteSpeechProjectorConfig * prevent a crash when re-saving/loading the model (line 109) * consider additional edge cases during preprocessing. * consider additional edge cases during preprocessing. * add features mask for batched inference (bugfix) * Minor refactor, remove multiaudio processor tests * Add set input/output embeddings for granite speech * Fix feature dim check in processor test * Pop input features in embed test for granite speech * Small fixes for test edge cases Add granite speech to seq2seq causal lm mapping names * Add small tests for granite speech model * Fix data parallelism test * Standardize model class names * Fix check for copies * Fix misaligned init check * Skip granite speech in checkpoint check * Use default for tie_word_embeddings in granite speech * Fix non documentation granite speech repo issues * Fix comments and docstring checks * Add placeholder docs for granite speech * Fix test naming collision * Code formatting * Rerun torch dummy obj regen * Fix save pretrained for granite speech * Import sorting * Fix tests typo * Remove offset hack * Pass args through encoder config * Remove unused prune heads from blip2 * removing einsum. replaced with explicit multiplication (relative positional encodings) and sdpa attention. * remove Sequential from ConformerFeedForward and ConformerConvModule. + fix for sdpa attention * remove GraniteSpeechConformerScale * rename to hidden_states * rename conformer layers to self.layers, remove the first linear from the list to keep the list homogenous. * move pre-norm to the attention/feedforward blocks (avoid complex module wrapping) * adding pre_norm into forward * feature extractor refactoring to resemble how it's done in phi4multimodal. * rename feature_extractor to audio_processor * bugfix: input_feature_mask fix to get the exact number tokens. * Fix pytest decorator in processor test * Add (disabled) integration tests for granite speech * Fix handling of optional feature masking * Loosen validation in processing for vLLM compatability * Formatting fixes * Update init structure to mirror llama * Make granite speech projector generic * Update test config to reflect generic projector * Formatting fixes * Fix typos, add license * Fix undefined var in input processing * Cleanup and expose ctc encoder * Add missing config docstrings * Better var names, type hints, etc * Set attn context size in init * Add max pos emb to encoder config * Cleanup feature extractor * Add granite speech architecture details * Remove granite speech qformer ref * Add paper link, explicit calc for qkv * Calculate padding directly in depthwise conv1d init * Raise value error instead of asserting * Reorder class defs (classes used at top) * Precompute relpos distances * Run formatting * Pass attention distances through forward * Apply suggestions from code review Co-authored-by: eustlb <94853470+eustlb@users.noreply.github.com> * Add todo for using common batch feature extraction * Rename audios/features * Ensure chat template may be provided to processor * Move granite speech docs to audio models * Add todos for input proc refactoring * Fix import order * Guard torch import * Use relative imports * Require torch backend for processor in granite speech * Add backend guards in feature extractor --------- Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com> Co-authored-by: Avihu Dekel <avihu.dekel@ibm.com> Co-authored-by: eustlb <94853470+eustlb@users.noreply.github.com> |
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Lysandre Debut
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54a123f068
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Simplify soft dependencies and update the dummy-creation process (#36827)
* Reverse dependency map shouldn't be created when test_all is set * [test_all] Remove dummies * Modular fixes * Update utils/check_repo.py Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com> * [test_all] Better docs * [test_all] Update src/transformers/commands/chat.py Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> * [test_all] Remove deprecated AdaptiveEmbeddings from the tests * [test_all] Doc builder * [test_all] is_dummy * [test_all] Import utils * [test_all] Doc building should not require all deps --------- Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com> Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> |
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DerekLiu35
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2527f71a47
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Add "selecting a quantization method" doc (#37159)
* initial draft * make documentation simpler * Update docs/source/en/quantization/selecting.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/selecting.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/selecting.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/selecting.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/selecting.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/selecting.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/selecting.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/selecting.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/selecting.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/selecting.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * turn pros and cons into tables * Apply suggestions from code review Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * add links to each quant method page * separate calibration vs no calibration methods * add calibration time estimates --------- Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> |
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Arthur
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e3eda6d188
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Add glm4 (#37388)
* add changed
* Revert "add changed"
This reverts commit
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Arthur
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25b7f27234
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Add llama4 (#37307)
* remove one of the last deps * update fast image processor after refactor * styling * more quality of life improvements * nit * update * cleanups * some cleanups * vllm updates * update fake image token * [convert] Fix typo * [convert] Strip extraneous bytes from shards * [convert] Minor fixes * [convert] Use num_experts * multi-image fixes in modeling + processor * fixup size * 128 experts * Use default rope * Unfuse mlp * simplify a lot inputs embeds merging * remove .item() 👀 * fix from review * Address feedback * Use None "default" for rope_scaling. Add eot. * set seed * return aspect ratios and bug fixes * Moe 128 rebased (#8) * 128 experts * Use default rope * Unfuse mlp * Address feedback * Use None "default" for rope_scaling. Add eot. * Meta/llama quant compat (#7) * add quant compatible model & conversion code for llama4 * fix a few issues * fix a few issues * minor type mapping fix --------- Co-authored-by: Lu Fang <fanglu@fb.com> * use a new config parameter to determine which model definition to use for MoE --------- Co-authored-by: Pedro Cuenca <pedro@huggingface.co> Co-authored-by: Lu Fang <fanglu@fb.com> * un-comment write_tokenizer from converting script * remove un-used imports * [llama4] Pop aspect_ratios from image processor output in Llama4Processor Signed-off-by: Jon Swenson <jmswen@gmail.com> * Fix parameter_count name * Update src/transformers/models/llama4/configuration_llama4.py * nit * Add changes for no_rope, moe_layers, chunked attention. Just need to test all * Update src/transformers/models/llama4/image_processing_llama4_fast.py * nit * fix post merge with main * support flex attention * fixes * fix * add layer * small updates * rebase and delete llm_compressor * nit * [llama4/mm] Add back <|image|> token that delimits global tile * [llama4/mm] Fix Llama 4 image processing unit tests * add explicit dtype Signed-off-by: Jon Swenson <jmswen@gmail.com> * sdpa works * comment todo small * fix model loading Signed-off-by: Zijing Liu <liuzijing2014@gmail.com> * revert * nits * small fix for TP on 1 node * Read new params from config * Add <|eom|> * lol don't know how this got here * adding fp8 * Save processor, fix chat template * style * Add boi/eoi tokens We don't use them. * fixes for now flex seems to work :) * updates * nits * updates * missking keys * add context parallel * update * update * fix * nits * add worldsize and make eager attn work for vision * Ignore new key present in base models * add tp_plan * fix nope Signed-off-by: Zijing Liu <liuzijing2014@gmail.com> * minor fix Signed-off-by: Zijing Liu <liuzijing2014@gmail.com> * Clean up Llama4 vision model * current updates * add support for `attn_temperature_tuning` * add floor scale * add missing attn scales * push what works, dirty trick for the device synch * oups * Fix pad_token_id See https://huggingface.co/ll-re/Llama-4-Scout-17B-16E/discussions/2/files Confirmed in the original codebase. * fix causallml loading * rm * fix tied-weights * fix sdpa * push current version * should work with both short and long * add compressed_tensos & fix fbgemm tp * Fix flex impl * style * chunking * try to revert the potentially breaking change * fix auto factory * fix shapes in general * rm processing * commit cache utils cleanup * Fix context length * fix * allocate * update tp_plan * fix SDPA! * Add support for sparse `Llama4TextMoe` layer from the kernel hub * cleanup * better merge * update * still broken fixing now * nits * revert print * Write max_position_embeddings and max_model_length * Update modeling_llama4.py * Save attention_chunk_size * Sync eos terminators * Read initializer_range * style * remove `dict` * fix * eager should use `chunked_attention_mask` * revert * fixup * fix config * Revert "Merge pull request #36 from huggingface/sparse-llama4-moe" This reverts commit |
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Bo Zheng
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6acd5aecb3
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Adding Qwen3 and Qwen3MoE (#36878)
* Initial commit for Qwen3 * fix and add tests for qwen3 & qwen3_moe * rename models for tests. * fix * fix * fix and add docs. * fix model name in docs. * simplify modular and fix configuration issues * Fix the red CI: ruff was updated * revert ruff, version was wrong * fix qwen3moe. * fix * make sure MOE can load * fix copies --------- Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com> |
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Minho Ryu
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eca74d1367
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[WIP] add deepseek-v3 (#35926)
* init commit
* style
* take comments into account
* add deepseekv3 modeling
* remove redundant code
* apply make style
* apply fix-copies
* make format
* add init files
* rename deepseekv3 into deepseek_v3 based on its model_type
* rename deepseekv3 into deepseek_v3 based on its model_type
* deepseek-v3 not deepseek_v3
* set model_type as deepseek_v3
* use default docs
* apply make
* fill type and docstring
* add rope_config_validation
* use custom DeepseekV3MLP
* hold code only for checkpoints congifuration; remove redundant
* revise rope yarn for DeepSeek variation
* rename DeepSeek-V3
* some refactoring
* revise load_hook to work properly; make moe func trainable; use llama instead of mixtral
* fix attention forward
* use -1 for not-changing dim when to use exapnd
* refactor DeepseekV3TopkRouter
* use reshape_for_rope instead of load_hook; revise attention forward for TP; rename q_head_dim with qk_head_dim
* register pre_hook and hook both
* make style
* use n_shared_experts
* Update src/transformers/models/deepseek_v3/configuration_deepseek_v3.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add test file
* update modeling_file according to modular file
* make style
* add mapping for DeepseekV3ForSequenceClassification
* remove aux_loss_alpha
* add deepseek_v3 for perf
* add deepseek_v3
* rename test as deepseekv3
* use tiny-deepseek-v3
* remove DeepseekV3ForSequenceClassification
* cache before padding
* remote output_router_logits
* Revert "remote output_router_logits"
This reverts commit
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Cyril Vallez
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788e1092e9
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Allow easy registration of custom attention functions (#36889)
* Update modeling_utils.py * style * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * add to init * Update modeling_utils.py * style * update * Update modeling_utils.py * Update modeling_utils.py * style * Add some doc * Update _toctree.yml * readd it for tgi/vllm compat * CIs * CIs |
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Cyril Vallez
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4303d88c09
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Add Phi4 multimodal (#36939)
* raw start * update * update * add to imports * update * up * simplify configs * clean configs * style * typos * Update convert_phi4_multimodal_weights_to_hf.py * Update convert_phi4_multimodal_weights_to_hf.py * fix * up * up * up * Update convert_phi4_multimodal_weights_to_hf.py * Update convert_phi4_multimodal_weights_to_hf.py * up * up * up * Update feature_extraction_phi4_multimodal.py * up * up * up * up * up * simplify configs * typo * cut code * typo * typo * typo * re * typo * up * up * up * add tests * fix * fix * Update test_modeling_phi4_multimodal.py * up * Update test_modeling_phi4_multimodal.py * doc * fix * up * up * up * up * up * up * simplify * up * simplify * config docstrings * cleanup * clean * typo * typo * fix * Update phi4_multimodal.md * fix * fix * Update test_modeling_phi4_multimodal.py * update * simplify reshapes and permutes * up * simplify special tokens * simplify processor a lot * Update processing_phi4_multimodal.py * Update processing_phi4_multimodal.py * switch to fast processor * image processor * Update image_processing_phi4_multimodal_fast.py * add lora extraction to converter * Update convert_phi4_multimodal_weights_to_hf.py * Update __init__.py * add AudioInput type in audio_utils * rewrite feature_extraction: support torch batched FFT * input_audio_embeds -> audio_input_features, input_image_embeds -> image_pixel_values * test update * not mono channel warning update * remove auto maps from processor * kargs dispatch in processor * simplify kwargs dispatch * simplify merging * remove default sampling rate * style * Update test_modeling_phi4_multimodal.py * update doc * doc * torch only feature extractor * make fake tokens adjustable * Update feature_extraction_phi4_multimodal.py * fix * Update processing_phi4_multimodal.py * simplify mask * last touch * fix copies * style * Update audio_utils.py * style * Update feature_extraction_phi4_multimodal.py * Update __init__.py * docstrings * copies * fix all checks * back to fix-copies * trigger CIs * Update feature_extraction_phi4_multimodal.py * improve tests with multimodal inputs * trigger CIs --------- Co-authored-by: Eustache Le Bihan <eulebihan@gmail.com> |
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Joao Gante
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949cca4061
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[CI] doc builder without custom image (#36862)
* no image * test * revert jax version updates * make fixup * update autodoc path for model_addition_debugger * shieldgemma2 * add missing pages to toctree |
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Haotong LIN
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6515c25953
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Add Prompt Depth Anything Model (#35401)
* add prompt depth anything model by modular transformer * add prompt depth anything docs and imports * update code style according transformers doc * update code style: import order issue is fixed by custom_init_isort * fix depth shape from B,1,H,W to B,H,W which is as the same as Depth Anything * move prompt depth anything to vision models in _toctree.yml * update backbone test; there is no need for resnet18 backbone test * update init file & pass RUN_SLOW tests * update len(prompt_depth) to prompt_depth.shape[0] Co-authored-by: Joshua Lochner <admin@xenova.com> * fix torch_int/model_doc * fix typo * update PromptDepthAnythingImageProcessor * fix typo * fix typo for prompt depth anything doc * update promptda overview image link of huggingface repo * fix some typos in promptda doc * Update image processing to include pad_image, prompt depth position, and related explanations for better clarity and functionality. * add copy disclaimer for prompt depth anything image processing * fix some format typos in image processing and conversion scripts * fix nn.ReLU(False) to nn.ReLU() * rename residual layer as it's a sequential layer * move size compute to a separate line/variable for easier debug in modular prompt depth anything * fix modular format for prompt depth anything * update modular prompt depth anything * fix scale to meter and some internal funcs warp * fix code style in image_processing_prompt_depth_anything.py * fix issues in image_processing_prompt_depth_anything.py * fix issues in image_processing_prompt_depth_anything.py * fix issues in prompt depth anything * update converting script similar to mllamma * update testing for modeling prompt depth anything * update testing for image_processing_prompt_depth_anything * fix assertion in image_processing_prompt_depth_anything * Update src/transformers/models/prompt_depth_anything/modular_prompt_depth_anything.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update src/transformers/models/prompt_depth_anything/modular_prompt_depth_anything.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update src/transformers/models/prompt_depth_anything/image_processing_prompt_depth_anything.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update src/transformers/models/prompt_depth_anything/image_processing_prompt_depth_anything.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update src/transformers/models/prompt_depth_anything/image_processing_prompt_depth_anything.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update docs/source/en/model_doc/prompt_depth_anything.md Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update docs/source/en/model_doc/prompt_depth_anything.md Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * update some testing * fix testing * fix * add return doc for forward of prompt depth anything * Update src/transformers/models/prompt_depth_anything/modular_prompt_depth_anything.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * Update tests/models/prompt_depth_anything/test_modeling_prompt_depth_anything.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * fix prompt depth order * fix format for testing prompt depth anything * fix minor issues in prompt depth anything doc * fix format for modular prompt depth anything * revert format for modular prompt depth anything * revert format for modular prompt depth anything * update format for modular prompt depth anything * fix parallel testing errors * fix doc for prompt depth anything * Add header * Fix imports * Licence header --------- Co-authored-by: Joshua Lochner <admin@xenova.com> Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> |
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fxmarty-amd
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1a374799ce
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Support loading Quark quantized models in Transformers (#36372)
* add quark quantizer * add quark doc * clean up doc * fix tests * make style * more style fixes * cleanup imports * cleaning * precise install * Update docs/source/en/quantization/quark.md Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update tests/quantization/quark_integration/test_quark.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/utils/quantization_config.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * remove import guard as suggested * update copyright headers * add quark to transformers-quantization-latest-gpu Dockerfile * make tests pass on transformers main + quark==0.7 * add missing F8_E4M3 and F8_E5M2 keys from str_to_torch_dtype --------- Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: Bowen Bao <bowenbao@amd.com> Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com> |
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Cyril Vallez
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e959530b8f
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Add Mistral3 (#36790)
* initial start
* style and dummies
* Create convert_mistral3_weights_to_hf.py
* update
* typo
* typo
* Update convert_mistral3_weights_to_hf.py
* Update convert_mistral3_weights_to_hf.py
* Update convert_mistral3_weights_to_hf.py
* Update convert_mistral3_weights_to_hf.py
* up
* Update convert_mistral3_weights_to_hf.py
* Update convert_mistral3_weights_to_hf.py
* update
* update
* Update image_processing_mistral3.py
* Update convert_mistral3_weights_to_hf.py
* fix patch merger
* Update convert_mistral3_weights_to_hf.py
* Update convert_mistral3_weights_to_hf.py
* up
* update modular to fit
* style
* Update convert_mistral3_weights_to_hf.py
* typo
* Update modular_mistral3.py
* simplify a lot all shape shenanigans
* simplify
* add working test processor
* Add partially working common modeling tests
* All tests working and remove mistral3 image processors
* add docs and fixup
* fix inference with image size >1540
* 🚨fix test image proc pixtral
* Remove vision_feature_select_strategy
* Update convert_mistral3_weights_to_hf.py
* Update convert_mistral3_weights_to_hf.py
* Update convert_mistral3_weights_to_hf.py
* Update convert_mistral3_weights_to_hf.py
* clean
* fix test checkpoints
* Update test_modeling_mistral3.py
* Update test_modeling_mistral3.py
* style
* Use Pixtral processor
* up
* finish cleaning processor to use pixtral directly
* Update __init__.py
* Update processing_pixtral.py
* doc
* Update __init__.py
* Update mistral3.md
* Update _toctree.yml
---------
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
Co-authored-by: yonigozlan <yoni.gozlan10@gmail.com>
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Arthur
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2829013d2d
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fix block mask typing (#36661)
* fix block mask typing * updated Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> * gemma * fix --------- Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> |
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Steven Liu
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e9756cdbc7
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[docs] Serving LLMs (#36522)
* initial * fix * model-impl |
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Arthur
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84f0186e89
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Add aya (#36521)
* initial commit * small fix * move stuff to image processing file * remove stuff in validate turn and fix return tensor * remove liquid stuff * in the process of addressing comments * changes to get the right tokenization * new __init__ works * fixing defulat std and mean * works * small testing scipt -- to be deleted before merge * remove redundant code * addressing comments * fix inits, add docs templates * refactor processor, switch to gotocr image processor * remove image proc from init * refactor to working llava-style architecture * Change AyaVisionModel to AyaVisionForConditionalGeneration * add tests * fixups * update doc * Adding logits_to_keep explicitly in ayavision forward to enable compatibility with cohere model * better variable names + remove code paths * Updates to aya_vision.md * address comments * adding copied from * make style and remove unused projector_hidden_act from config * sort init * include usage of fast image proc and proc on cuda in doc * update checkpoint iin test processor * update checkpoint in test processor 2 * remove test_model and update docstring * skip failing tests --------- Co-authored-by: Saurabh Dash <saurabh@cohere.com> Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co> |
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Steven Liu
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c0f8d055ce
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[docs] Redesign (#31757)
* toctree * not-doctested.txt * collapse sections * feedback * update * rewrite get started sections * fixes * fix * loading models * fix * customize models * share * fix link * contribute part 1 * contribute pt 2 * fix toctree * tokenization pt 1 * 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> * "to be not" -> "not to be" (#32636) * "to be not" -> "not to be" * Update sam.md * Update trainer.py * Update modeling_utils.py * Update test_modeling_utils.py * Update test_modeling_utils.py * fix hfoption tag * tokenization pt. 2 * image processor * fix toctree * backbones * feature extractor * fix file name * processor * update not-doctested * update * make style * fix toctree * revision * make fixup * fix toctree * fix * make style * fix hfoption tag * pipeline * pipeline gradio * pipeline web server * add pipeline * fix toctree * not-doctested * prompting * llm optims * fix toctree * fixes * cache * text generation * fix * chat pipeline * chat stuff * xla * torch.compile * cpu inference * toctree * gpu inference * agents and tools * gguf/tiktoken * finetune * toctree * trainer * trainer pt 2 * optims * optimizers * accelerate * parallelism * fsdp * update * distributed cpu * hardware training * gpu training * gpu training 2 * peft * distrib debug * deepspeed 1 * deepspeed 2 * chat toctree * quant pt 1 * quant pt 2 * fix toctree * fix * fix * quant pt 3 * quant pt 4 * serialization * torchscript * scripts * tpu * review * model addition timeline * modular * more reviews * reviews * fix toctree * reviews reviews * continue reviews * more reviews * modular transformers * more review * zamba2 * fix * all frameworks * pytorch * supported model frameworks * flashattention * rm check_table * not-doctested.txt * rm check_support_list.py * feedback * updates/feedback * review * feedback * fix * update * feedback * updates * update --------- Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com> |
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Pavel Iakubovskii
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a957b7911a
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Add SigLIP 2 (#36323)
* Docs * Inits * Auto classes * Add siglip base * Add base tests * Fix Siglip V1 for fix res version * Add image processor * Update conversion * Experimenting with vectorized embeddings * Fixup * Add modular Siglip2Processor * Add modular configuration * Rename num patches * Correct image and text features merging * Working conversion script * Refactoring conversion script * Remove unused code in conversion script * Shorten dict a bit * Refactoring conversion * Done conversion refactoring * Fixup * Modular siglip2 * Make model exportable and compilable without graph breaks * Remove position_ids from image_processor * REmove position ids from modeling file * Update modular * Type hint * Fixup * Set defaults to processor * Add integration test * Revert spatial shapes back to tensor * Change order * Fix most of the tests * Fix docstring * Remove interpolate_pos_encoding arg (not needed) * Update docs * Standardize processing * Fix attention_mask in vision head * Siglip v1: remove double transpose in FA2 * Update modular file * Update FA2 test * Update expected logits * Fix interpolation for siglip2 image processor * Skip init test * Skip dispatch on flash test * Fix modeling tests * Fixup * Add dummy objects * Fix some docstrings * Add siglip2 in index.md * Fix consistency * Add docs * Remove size and data format * Add image processor tests * Fix * Add fast image processor * Fix style * Fix * Docs * Set lowercase for tokenizer * Adjust head size for Siglip v1 * Update siglip2 for consistency with siglip1 * Update siglip2 conversion * Update pipeline * Update checkpoints in tests * Update checkpoint name * Fix pooling for image classification model * Fix FA2 test * Update processor * Fix check repo * Update docs * Fix typos * Fix docstring for fast image processor * Add siglip2 to FA2 docs * Fix fast ip tests * Fix constitency * Fix tokenizer class for siglip v1 * Fix missing header * Refactor scaling for clip, siglip, siglip2 * Remove unused imports * Make fast IP default for siglip2 * Update docs * Update checkpoints * Update modular * Update paper link * Fixup * Fix name in toctree * Fix test |
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Joao Gante
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27d1707586
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[smolvlm] make CI green (#36306)
* add smolvlm to toctree * add requirements * dev-ci * no docker changes * dev-ci * update torch-light.dockerfile * derp * dev-ci |
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Mayank Mishra
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a570e2ba87
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add shared experts for upcoming Granite 4.0 language models (#35894)
* Modular GraniteMoE with shared Experts. Signed-off-by: Shawn Tan <shawntan@ibm.com> * Modified * Import order. * Modified for style * Fix space. * Test * Remove extra granitemoe file. * New converted file and tests * Modified __init__ files. * Formatting. * Dummy PT objects * register granitemoe shared model Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> * fix linting of a file Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> * fix import in modeling file Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> * update generated modeling file Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> * add documentation Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> * update docstrings Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> * update generated modeling file Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> * fix docstrings in config class Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> * merge main Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> --------- Signed-off-by: Shawn Tan <shawntan@ibm.com> Signed-off-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> Co-authored-by: Shawn Tan <shawntan@ibm.com> Co-authored-by: Shawn Tan <shawn@wtf.sg> Co-authored-by: Sukriti-Sharma4 <sukriti.sharma4@ibm.com> Co-authored-by: Sukriti Sharma <Ssukriti@users.noreply.github.com> |
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Raushan Turganbay
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1931a35140
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Chat template docs (#36163)
* decompose chat template docs * add docs * update model docs * qwen2-5 * pixtral * remove old chat template * also video as list frames supported * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/chat_template_multimodal.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * remove audio for now --------- Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> |
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Elvir Crnčević
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845b0a2616
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Efficient Inference Kernel for SpQR (#34976)
* Resolve vptq conflict * Rename spqr package to spqr_quant * Get rid of aqlm mention * Start working on tests * Resolve ruff code checks * Ruff format * Isort * Test updates * Add gpu tag * Rename to modules_to_not_convert * Config update * Docs and config update * Docs and config update * Update to update_torch_dtype * spqr config parameter validation * Ruff update * Apply ruff fixes * Test fixes * Ruff update * Mark tests as @slow again; Ruff; Docstring update * Ruff * Remove absolute path * Resolve typo * Remove redundandt log * Check accelerate/spqr availability * Ruff fix * Check if the config contains proper shapes * Ruff test * Documentation update * overview update * Ruff checks * Ruff code quality * Make style * Update docs/source/en/quantization/spqr.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update spqr.md * Enable gptqmodel (#35012) * gptqmodel Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update readme Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * gptqmodel need use checkpoint_format (#1) * gptqmodel need use checkpoint_format * fix quantize * Update quantization_config.py * Update quantization_config.py * Update quantization_config.py --------- Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> * Revert quantizer_gptq.py (#2) * revert quantizer_gptq.py change * pass **kwargs * limit gptqmodel and optimum version Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix warning Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix version check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * revert unrelated changes Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * enable gptqmodel tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix requires gptq Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * Fix Transformer compat (#3) * revert quantizer_gptq.py change * pass **kwargs * add meta info * cleanup * cleanup * Update quantization_config.py * hf_select_quant_linear pass checkpoint_format and meta * fix GPTQTestCUDA * Update test_gptq.py * gptqmodel.hf_select_quant_linear() now does not select ExllamaV2 * cleanup * add backend * cleanup * cleanup * no need check exllama version * Update quantization_config.py * lower checkpoint_format and backend * check none * cleanup * Update quantization_config.py * fix self.use_exllama == False * spell * fix unittest * fix unittest --------- Co-authored-by: LRL <lrl@lbx.dev> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format again Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update gptqmodel version (#6) * update gptqmodel version * update gptqmodel version * fix unit test (#5) * update gptqmodel version * update gptqmodel version * "not self.use_exllama" is not equivalent to "self.use_exllama==False" * fix unittest * update gptqmodel version * backend is loading_attibutes (#7) * fix format and tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix memory check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix device mismatch Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix result check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * update tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * review: update docs (#10) * review: update docs (#12) * review: update docs * fix typo * update tests for gptqmodel Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update document (#9) * update overview.md * cleanup * Update overview.md * Update overview.md * Update overview.md * update gptq.md * Update gptq.md * Update gptq.md * Update gptq.md * Update gptq.md * Update gptq.md * Update gptq.md --------- Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> * typo * doc note for asymmetric quant * typo with apple silicon(e) * typo for marlin * column name revert: review * doc rocm support * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/overview.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/overview.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> --------- Signed-off-by: jiqing-feng <jiqing.feng@intel.com> Co-authored-by: LRL-ModelCloud <165116337+LRL-ModelCloud@users.noreply.github.com> Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> Co-authored-by: ZX-ModelCloud <165115237+ZX-ModelCloud@users.noreply.github.com> Co-authored-by: LRL <lrl@lbx.dev> Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com> Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Fix : Nemotron Processor in GGUF conversion (#35708) * fixing nemotron processor * make style * Update docs/source/en/quantization/spqr.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Add missing TOC to doc --------- Signed-off-by: jiqing-feng <jiqing.feng@intel.com> Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by: jiqing-feng <jiqing.feng@intel.com> Co-authored-by: LRL-ModelCloud <165116337+LRL-ModelCloud@users.noreply.github.com> Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> Co-authored-by: ZX-ModelCloud <165115237+ZX-ModelCloud@users.noreply.github.com> Co-authored-by: LRL <lrl@lbx.dev> Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Mohamed Mekkouri
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efe72fe21f
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Adding FP8 Quantization to transformers (#36026)
* first commit * adding kernels * fix create_quantized_param * fix quantization logic * end2end * fix style * fix imports * fix consistency * update * fix style * update * udpate after review * make style * update * update * fix * update * fix docstring * update * update after review * update * fix scheme * update * update * fix * update * fix docstring * add source * fix test --------- Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> |
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Armaghan Shakir
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9a6be63fdb
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Add Apple's Depth-Pro for depth estimation (#34583)
* implement config and model building blocks * refactor model architechture * update model outputs * update init param to include use_fov_model * update param name in config * fix hidden_states and attentions outputs for fov * sort config * complete minor todos * update patching * update config for encoder * fix config * use correct defaults in config * update merge for compatibility with different image size * restructure encoder for custom configuration * make fov model compatible with custom config * replace word "decoder" with "fusion" * weight conversion script * fix fov squeeze * update conversion script (without test) * upload ruff image processing * create fast image processing * use torch interpolation for image processing * complete post_process_depth_estimation * config: fix imports and sort args * apply inference in weight conversion * use mllama script instead for weight conversion * clean weight conversion script * add depth-pro status in other files * fill docstring in config * formatting * more formatting * formatting with ruff * formatting with style * fix copied classes * add examples; update weight convert script * fix using check_table.py and isort * fix config docstring * add depth pro to sdpa docs * undo unintentional changes in configuration_gemma.py * minor fixes * test image processing * fixes and tests * more fixes * use output states from image_encoder instead * Revert "use output states from image_encoder instead" This reverts commit |
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Jade Choghari
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006d9249ec
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Adding RT-DETRv2 for object detection (#34773)
* cookiecutter add rtdetrv2 * make modular working * working modelgit add . * working modelgit add . * finalize moduar inheritence * finalize moduar inheritence * Update src/transformers/models/rtdetrv2/modular_rtdetrv2.py Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> * update modular and add rename * remove output ckpt * define loss_kwargs * fix CamelCase naming * fix naming + files * fix modular and convert file * additional changes * fix modular * fix import error (switch to lazy) * fix autobackbone * make style * add * update testing * fix loss * remove old folder * fix testing for v2 * update docstring * fix docstring * add resnetv2 (with modular bug to fix) * remove resnetv2 backbone * fix changes * small fixes * remove rtdetrv2resnetconfig * add rtdetrv2 name to convert * make style * Update docs/source/en/model_doc/rt_detr_v2.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update src/transformers/models/rt_detr_v2/modular_rt_detr_v2.py Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update src/transformers/models/rt_detr_v2/modular_rt_detr_v2.py Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * fix modular typo after review * add reviewed changes * add final review changes * Update docs/source/en/model_doc/rt_detr_v2.md Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> * Update src/transformers/models/rt_detr_v2/__init__.py Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> * Update src/transformers/models/rt_detr_v2/convert_rt_detr_v2_weights_to_hf.py Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> * add review changes * remove rtdetrv2 resnet * removing this weird project change * change ckpt name from jadechoghari to author * implement review and update testing * update naming and remove wrong ckpt * name * make fix-copies * Fix RT-DETR loss * Add resources, fix name * Fix repo in docs * Fix table name --------- Co-authored-by: jadechoghari <jadechoghari@users.noreply.huggingface.co> Co-authored-by: Cyril Vallez <cyril.vallez@gmail.com> Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by: qubvel <qubvel@gmail.com> |
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David
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8d73a38606
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Add DAB-DETR for object detection (#30803)
* initial commit * encoder+decoder layer changes WIP * architecture checks * working version of detection + segmentation * fix modeling outputs * fix return dict + output att/hs * found the position embedding masking bug * pre-training version * added iamge processors * typo in init.py * iterupdate set to false * fixed num_labels in class_output linear layer bias init * multihead attention shape fixes * test improvements * test update * dab-detr model_doc update * dab-detr model_doc update2 * test fix:test_retain_grad_hidden_states_attentions * config file clean and renaming variables * config file clean and renaming variables fix * updated convert_to_hf file * small fixes * style and qulity checks * return_dict fix * Merge branch main into add_dab_detr * small comment fix * skip test_inputs_embeds test * image processor updates + image processor test updates * check copies test fix update * updates for check_copies.py test * updates for check_copies.py test2 * tied weights fix * fixed image processing tests and fixed shared weights issues * added numpy nd array option to get_Expected_values method in test_image_processing_dab_detr.py * delete prints from test file * SafeTensor modification to solve HF Trainer issue * removing the safetensor modifications * make fix copies and hf uplaod has been added. * fixed index.md * fixed repo consistency * styel fix and dabdetrimageprocessor docstring update * requested modifications after the first review * Update src/transformers/models/dab_detr/image_processing_dab_detr.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * repo consistency has been fixed * update copied NestedTensor function after main merge * Update src/transformers/models/dab_detr/modeling_dab_detr.py Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> * temp commit * temp commit2 * temp commit 3 * unit tests are fixed * fixed repo consistency * updated expected_boxes varible values based on related notebook results in DABDETRIntegrationTests file. * temporarialy config modifications and repo consistency fixes * Put dilation parameter back to config * pattern embeddings have been added to the rename_keys method * add dilation comment to config + add as an exception in check_config_attributes SPECIAL CASES * delete FeatureExtractor part from docs.md * requested modifications in modeling_dab_detr.py * [run_slow] dab_detr * deleted last segmentation code part, updated conversion script and changed the hf path in test files * temp commit of requested modifications * temp commit of requested modifications 2 * updated config file, resolved codepaths and refactored conversion script * updated decodelayer block types and refactored conversion script * style and quality update * small modifications based on the request * attentions are refactored * removed loss functions from modeling file, added loss function to lossutils, tried to move the MLP layer generation to config but it failed * deleted imageprocessor * fixed conversion script + quality and style * fixed config_att * [run_slow] dab_detr * changing model path in conversion file and in test file * fix Decoder variable naming * testing the old loss function * switched back to the new loss function and testing with the odl attention functions * switched back to the new last good result modeling file * moved back to the version when I asked the review * missing new line at the end of the file * old version test * turn back to newest mdoel versino but change image processor * style fix * style fix after merge main * [run_slow] dab_detr * [run_slow] dab_detr * added device and type for head bias data part * [run_slow] dab_detr * fixed model head bias data fill * changed test_inference_object_detection_head assertTrues to torch test assert_close * fixes part 1 * quality update * self.bbox_embed in decoder has been restored * changed Assert true torch closeall methods to torch testing assertclose * modelcard markdown file has been updated * deleted intemediate list from decoder module --------- Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com> |
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Yoni Gozlan
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2b46943195
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Add GOT-OCR 2.0 to Transformers (#34721)
* init modular got_ocr2 * Get correct got_ocr architecture * add processing * run modular with processing * add working inference * apply modular * Refactor and fix style * Refactor, cleanup, fix style * fix init order * Fix docs * add base modeling tests * fix style and consistency * rename doc file * fix repo consistency * fix inference with box * add image processing and support for crop_to_multi_page * Fix batch inference * add tests * fixup * fix slow test * fix docstrings * Add model doc * update to new init * fix input autocast pixel_values dtype * update doc * move doc to multimodal * Reformat crop_image_to_patches and add docstrings * Fix example in forward docstring * Address Pablo review * [run slow] got_ocr2 * remove defaults defined twice * apply modular * add torch_device to integration tests * update modular * follow-up Pavel review * add device variable in doc * fix doc multi-page * Force eager attention for vision encoder to avoid attn implementation conflict * revert qwen2vl doc changes * use Qwen2ForCausalLM instead of Qwen2Model * make fixup * refactor gotocr2 to llava style * uniformize function names and reduce checks * final nits * fix pixel_values dtype error * change checkpoint names * fix modular |
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Matt
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414658f94f
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Close Zamba2Config code block (#35914)
* close zamba2 code block * Add Zamba2 to toctree |
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Alex Brooks
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71cc8161b2
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Granite Vision Support (#35579)
* Add multimodal granite support Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> Support multiple image feature layres Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Remove failing validation for visual encoders with no cls Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Update llava based models / configs to support list of feature layers Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Add tests for multiple feature layers Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Use conditional instead of except for misaligned feature shapes Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com> * crop cls from each hidden state Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com> * Fix formatting Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Support single vision feature int in vipllava Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> * Fix typo in vision feature selection strategy validation Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com> * Add tentative integration test for granite vision models Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com> * Add granite vision docs Replace multimodal granite refs with granite vision Add granite vision / llava next alias Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com> * Use image url in granitevision example Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com> --------- Signed-off-by: Alex-Brooks <Alex.Brooks@ibm.com> Signed-off-by: Alex-Brooks <Alex.brooks@ibm.com> |
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ShuaiBai623
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f3f6c86582
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add qwen2.5vl (#35569)
* add qwen2.5vl * fix * pass check table * add modular file * fix style * Update src/transformers/models/qwen2_5_vl/modeling_qwen2_5_vl.py Co-authored-by: Minho Shim <6764739+minostauros@users.noreply.github.com> * Update src/transformers/models/qwen2_5_vl/modeling_qwen2_5_vl.py Co-authored-by: Minho Shim <6764739+minostauros@users.noreply.github.com> * Update src/transformers/models/qwen2_5_vl/modeling_qwen2_5_vl.py Co-authored-by: Minho Shim <6764739+minostauros@users.noreply.github.com> * padd copy check * use modular * fix * fix * fix * update flashatt2&sdpa support_list * Update docs/source/en/_toctree.yml Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/qwen2_5_vl.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/qwen2_5_vl.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/qwen2_5_vl.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/qwen2_5_vl.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update src/transformers/models/qwen2_5_vl/modular_qwen2_5_vl.py Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * update config * update * fix hf path * rename Qwen2_5_VLVideosKwargs * fix * fix * update * excuted modular * rollback init * fix * formated * simpler init * fix * fix * fix * fix * fix * update docs * fix * fix * update Qwen2VLRotaryEmbedding for yarn * fix --------- Co-authored-by: Minho Shim <6764739+minostauros@users.noreply.github.com> Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by: gewenbin0992 <gewenbin292@163.com> Co-authored-by: gewenbin0992 <67409248+gewenbin0992@users.noreply.github.com> |
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Joao Gante
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90b46e983f
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Remove old benchmark code (#35730)
* remove traces of the old deprecated benchmarks * also remove old tf benchmark example, which uses deleted code * run doc builder |
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eustlb
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3df90103b8
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move fastspeech to audio models (#35788) | ||
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eustlb
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5f0f4b1b93
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Patch moonshine (#35731)
* udpate expected logits for T4 runners * update doc * correct order of the args for better readability * remove generate wrap * convert modular |
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StevenBucaille
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abe57b6f17
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Add SuperGlue model (#29886)
* Initial commit with template code generated by transformers-cli
* Multiple additions to SuperGlue implementation :
- Added the SuperGlueConfig
- Added the SuperGlueModel and its implementation
- Added basic weight conversion script
- Added new ImageMatchingOutput dataclass
* Few changes for SuperGlue
* Multiple changes :
- Added keypoint detection config to SuperGlueConfig
- Completed convert_superglue_to_pytorch and succesfully run inference
* Reverted unintentional change
* Multiple changes :
- Added SuperGlue to a bunch of places
- Divided SuperGlue into SuperGlueForImageMatching and SuperGlueModel
- Added testing images
* Moved things in init files
* Added docs (to be finished depending on the final implementation)
* Added necessary imports and some doc
* Removed unnecessary import
* Fixed make fix-copies bug and ran it
* Deleted SuperGlueModel
Fixed convert script
* Added SuperGlueImageProcessor
* Changed SuperGlue to support batching pairs of images and modified ImageMatchingOutput in consequences
* Changed convert_superglue_to_hf.py script to experiment different ways of reading an image and seeing its impact on performances
* Added initial tests for SuperGlueImageProcessor
* Added AutoModelForImageMatching in missing places and tests
* Fixed keypoint_detector_output instructions
* Fix style
* Adapted to latest main changes
* Added integration test
* Fixed bugs to pass tests
* Added keypoints returned by keypoint detector in the output of SuperGlue
* Added doc to SuperGlue
* SuperGlue returning all attention and hidden states for a fixed number of keypoints
* Make style
* Changed SuperGlueImageProcessor tests
* Revert "SuperGlue returning all attention and hidden states for a fixed number of keypoints"
Changed tests accordingly
This reverts commit 5b3b669c
* Added back hidden_states and attentions masked outputs with tests
* Renamed ImageMatching occurences into KeypointMatching
* Changed SuperGlueImageProcessor to raise error when batch_size is not even
* Added docs and clarity to hidden state and attention grouping function
* Fixed some code and done refactoring
* Fixed typo in SuperPoint output doc
* Fixed some of the formatting and variable naming problems
* Removed useless function call
* Removed AutoModelForKeypointMatching
* Fixed SuperGlueImageProcessor to only accept paris of images
* Added more fixes to SuperGlueImageProcessor
* Simplified the batching of attention and hidden states
* Simplified stack functions
* Moved attention instructions into class
* Removed unused do_batch_norm argument
* Moved weight initialization to the proper place
* Replaced deepcopy for instantiation
* Fixed small bug
* Changed from stevenbucaille to magic-leap repo
* Renamed London Bridge images to Tower Bridge
* Fixed formatting
* Renamed remaining "london" to "tower"
* Apply suggestions from code review
Small changes in the docs
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Added AutoModelForKeypointMatching
* Changed images used in example
* Several changes to image_processing_superglue and style
* Fixed resample type hint
* Changed SuperGlueImageProcessor and added test case for list of 2 images
* Changed list_of_tuples implementation
* Fix in dummy objects
* Added normalize_keypoint, log_sinkhorn_iterations and log_optimal_transport docstring
* Added missing docstring
* Apply suggestions from code review
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>
* Moved forward block at bottom
* Added docstring to forward method
* Added docstring to match_image_pair method
* Changed test_model_common_attributes to test_model_get_set_embeddings test method signature
* Removed AutoModelForKeypointMatching
* Removed image fixtures and added load_dataset
* Added padding of images in SuperGlueImageProcessor
* Cleaned up convert_superglue_to_hf script
* Added missing docs and fixed unused argument
* Fixed SuperGlueImageProcessor tests
* Transposed all hidden states from SuperGlue to reflect the standard (..., seq_len, feature_dim) shape
* Added SuperGlueForKeypointMatching back to modeling_auto
* Fixed image processor padding test
* Changed SuperGlue docs
* changes:
- Abstraction to batch, concat and stack of inconsistent tensors
- Changed conv1d's to linears to match standard attention implementations
- Renamed all tensors to be tensor0 and not tensor_0 and be consistent
- Changed match image pair to run keypoint detection on all image first, create batching tensors and then filling these tensors matches after matches
- Various changes in docs, etc
* Changes to SuperGlueImageProcessor:
- Reworked the input image pairs checking function and added tests accordingly
- Added Copied from statements
- Added do_grayscale tag (also for SuperPointImageProcessor)
- Misc changes for better code
* Formatting changes
* Reverted conv1d to linear conversion because of numerical differences
* fix: changed some code to be more straightforward (e.g. filtering keypoints) and converted plot from opencv to matplotlib
* fix: removed unnecessary test
* chore: removed commented code and added back hidden states transpositions
* chore: changed from "inconsistent" to "ragged" function names as suggested
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* docs: applied suggestions
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* docs: updated to display matched output
* chore: applied suggestion for check_image_pairs_input function
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* chore: changed check_image_pairs_input function name to validate_and_format_image_pairs and used validate_preprocess_arguments function
* tests: simplified tests for image input format and shapes
* feat: converted SuperGlue's use of Conv1d with kernel_size of 1 with Linear layers. Changed tests and conversion script accordingly
* feat: several changes to address comments
Conversion script:
- Reverted fuse batchnorm to linear conversion
- Changed all 'nn.Module' to respective SuperGlue models
- Changed conversion script to use regex mapping and match other recent scripts
Modeling SuperGlue:
- Added batching with mask and padding to attention
- Removed unnecessary concat, stack and batch ragged pairs functions
- Reverted batchnorm layer
- Renamed query, key, value and merge layers into q, k, v, out proj
- Removed Union of different Module into nn.Module in _init_weights method typehint
- Changed several method's signature to combine image0 and image1 inputs with appropriate doc changes
- Updated SuperGlue's doc with torch.no_grad()
Updated test to reflect changes in SuperGlue model
* refactor: changed validate_and_format_image_pairs function with clarity
* refactor: changed from one SuperGlueMLP class to a list of SuperGlueMLP class
* fix: fixed forgotten init weight change from last commit
* fix: fixed rebase mistake
* fix: removed leftover commented code
* fix: added typehint and changed some of arguments default values
* fix: fixed attribute default values for SuperGlueConfig
* feat: added SuperGlueImageProcessor post process keypoint matching method with tests
* fix: fixed SuperGlue attention and hidden state tuples aggregation
* chore: fixed mask optionality and reordered tensor reshapes to be cleaner
* chore: fixed docs and error message returned in validate_and_format_image_pairs function
* fix: fixed returned keypoints to be the ones that SuperPoint returns
* fix: fixed check on number of image sizes for post process compared to the pairs in outputs of SuperGlue
* fix: fixed check on number of image sizes for post process compared to the pairs in outputs of SuperGlue (bis)
* fix: Changed SuperGlueMultiLayerPerceptron instantiation to avoid if statement
* fix: Changed convert_superglue_to_hf script to reflect latest SuperGlue changes and got rid of nn.Modules
* WIP: implement Attention from an existing class (like BERT)
* docs: Changed docs to include more appealing matching plot
* WIP: Implement Attention
* chore: minor typehint change
* chore: changed convert superglue script by removing all classes and apply conv to linear conversion in state dict + rearrange keys to comply with changes in model's layers organisation
* Revert "Fixed typo in SuperPoint output doc"
This reverts commit
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Arthur
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c23a1c1932
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Add-helium (#35669)
* Add the helium model. * Add a missing helium. * And add another missing helium. * Use float for the rmsnorm mul. * Add the Helium tokenizer converter. * Add the pad token as suggested by Arthur. * Update the RMSNorm + some other tweaks. * Fix more rebase issues. * fix copies and style * fixes and add helium.md * add missing tests * udpate the backlink * oups * style * update init, and expected results * small fixes * match test outputs * style fixup, fix doc builder * add dummies and we should be good to go!z * update sdpa and fa2 documentation --------- Co-authored-by: laurent <laurent.mazare@gmail.com> |
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Raushan Turganbay
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52e1f87c7d
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[WIP] Emu3: add model (#33770)
* model can convert to HF and be loaded back * nit * works in single batch generation but hallucinates * use the image tokens * add image generation * now it works * add tests * update * add modulare but it doesn't work for porting docstring :( * skip some tests * add slow tests * modular removed the import? * guess this works * update * update * fix copies * fix test * fix copies * update * docs * fix tests * last fix tests? * pls * repo consistency * more style * style * remove file * address comments * tiny bits * update after the new modular * fix tests * add one more cond in check attributes * decompose down/up/mid blocks * allow static cache generation in VLMs * nit * fix copies * Update docs/source/en/model_doc/emu3.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/emu3.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/emu3.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/emu3.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/emu3.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/emu3.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/emu3.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/model_doc/emu3.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * fix VAE upsampling * Update src/transformers/models/emu3/modular_emu3.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * address comments * state overwritten stuff explicitly * fix copies * add the flag for flex attn --------- Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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eustlb
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5f087d1335
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Add Moonshine (#34784)
* config draft * full encoder forward * full decoder forward * fix sdpa and FA2 * fix sdpa and FA2 * moonshine model * moonshine model forward * fix attention with past_key_values * add MoonshineForConditionalGeneration * fix cache handling and causality for cross attention * no causal attention mask for the encoder * model addition (imports etc) * small nit * nits * Update src/transformers/models/moonshine/convert_usefulsensors_to_hf.py Co-authored-by: Joshua Lochner <admin@xenova.com> * add rope_theta * nits * model doc * Update src/transformers/models/auto/configuration_auto.py Co-authored-by: Joshua Lochner <admin@xenova.com> * imports * add MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING_NAMES * updates modular * make * make fix-copies * ruff check examples fix * fix check_modular_conversion * nit * nits * nits * copied from -> imports * imports fix * integrate attention refacto * modular edge case * remove encoder * convolutions params in config * run modular_model_converter * make * Update docs/source/en/model_doc/moonshine.md Co-authored-by: Joshua Lochner <admin@xenova.com> * MoonshineModelTest * correct typo * make style * integration tests * make * modular convert * name conversion update (up_proj -> fc1 etc) * update config * update MLP * update attention * update encoder layer * update decoder layer * update convolutions parameters * update encoder * remove INPUTS_DOCSTRING * update decoder * update conditional generation * update pretrained model * imports * modular converted * update doc * fix * typo * update doc * update license * update init * split config in file * two classes for MLP * attention from GLM * from GlmRotaryEmbedding * split MLP * apply arthur's review suggestions * apply arthur's review suggestions * apply arthur's review suggestions * auto feature extractor * convert modular * fix + make * convert modular * make * unsplit config * use correct checkpoint * wrap generate * update tests * typos * make * typo * update doc --------- Co-authored-by: Joshua Lochner <admin@xenova.com> |
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Benjamin Warner
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1e3ddcb2d0
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ModernBERT bug fixes (#35404)
* bug fixes
* organize imports
* wrap cpu warning in reference_compile
* Avoid needing repad_logits_with_grad, always repad with grads when training
I'm not 100% that the conditional with "or labels is None" makes sense though - not sure what the intention is there. Perhaps we can remove that?
* Revert "Avoid needing repad_logits_with_grad, always repad with grads when training"
This reverts commit
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DaNing An
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4c2c12b3de
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[docs] Remove Hiera from AUDIO MODELS in docs (#35544)
Remove Hiera from AUDIO MODELS Hiera is a visual model and should not appear in audio model... |
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NielsRogge
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8490d3159c
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Add ViTPose (#30530)
* First draft * Make fixup * Make forward pass worké * Improve code * More improvements * More improvements * Make predictions match * More improvements * Improve image processor * Fix model tests * Add classic decoder * Convert classic decoder * Verify image processor * Fix classic decoder logits * Clean up * Add post_process_pose_estimation * Improve post_process_pose_estimation * Use AutoBackbone * Add support for MoE models * Fix tests, improve num_experts% * Improve variable names * Make fixup * More improvements * Improve post_process_pose_estimation * Compute centers and scales * Improve postprocessing * More improvements * Fix ViTPoseBackbone tests * Add docstrings, fix image processor tests * Update index * Use is_cv2_available * Add model to toctree * Add cv2 to doc tests * Remove script * Improve conversion script * Add coco_to_pascal_voc * Add box_to_center_and_scale to image_transforms * Update tests * Add integration test * Fix merge * Address comments * Replace numpy by pytorch, improve docstrings * Remove get_input_embeddings * Address comments * Move coco_to_pascal_voc * Address comment * Fix style * Address comments * Fix test * Address comment * Remove udp * Remove comment * [WIP] need to check if the numpy function is same as cv * add scipy affine_transform * Update src/transformers/models/vitpose/image_processing_vitpose.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * refactor convert * add output_shape * add atol 5e-2 * Use hf_hub_download in conversion script * make box_to_center more applicable * skipt test_get_set_embedding * fix to accept array and fix CI * add co-contributor * make it to tensor type output * add torch * change to torch tensor * add more test * minor change * CI test change * import torch should be above ImageProcessor * make style * try not use torch in def * Update src/transformers/models/vitpose/image_processing_vitpose.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/vitpose_backbone/configuration_vitpose_backbone.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/vitpose_backbone/modeling_vitpose_backbone.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/vitpose/modeling_vitpose.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * fix * fix * add caution * make more detail about dataset_index * Update src/transformers/models/vitpose/modeling_vitpose.py Co-authored-by: Sangbum Daniel Choi <34004152+SangbumChoi@users.noreply.github.com> * Update src/transformers/models/vitpose/image_processing_vitpose.py Co-authored-by: Sangbum Daniel Choi <34004152+SangbumChoi@users.noreply.github.com> * add docs * Update docs/source/en/model_doc/vitpose.md * Update src/transformers/models/vitpose/configuration_vitpose.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/__init__.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Revert "Update src/transformers/__init__.py" This reverts commit |
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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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Andrei Panferov
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64c05eecd6
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HIGGS Quantization Support (#34997)
* higgs init * working with crunches * per-model workspaces * style * style 2 * tests and style * higgs tests passing * protecting torch import * removed torch.Tensor type annotations * torch.nn.Module inheritance fix maybe * hide inputs inside quantizer calls * style structure something * Update src/transformers/quantizers/quantizer_higgs.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * reworked num_sms * Update src/transformers/integrations/higgs.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * revamped device checks * docstring upd * Update src/transformers/quantizers/quantizer_higgs.py Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com> * edited tests and device map assertions * minor edits * updated flute cuda version in docker * Added p=1 and 2,3bit HIGGS * flute version check update * incorporated `modules_to_not_convert` * less hardcoding * Fixed comment * Added docs * Fixed gemma support * example in docs * fixed torch_dtype for HIGGS * Update docs/source/en/quantization/higgs.md Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Collection link * dequantize interface * newer flute version, torch.compile support * unittest message fix * docs update compile * isort * ValueError instead of assert --------- Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com> |
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wejoncy
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4e27a4009d
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FEAT : Adding VPTQ quantization method to HFQuantizer (#34770)
* init vptq
* add integration
* add vptq support
fix readme
* add tests && format
* format
* address comments
* format
* format
* address comments
* format
* address comments
* remove debug code
* Revert "remove debug code"
This reverts commit
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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> |