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358 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
NielsRogge
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d47cdae27e
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[Docs] Move models to appropriate section (#37338)
* Move models * update --------- Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com> Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> |
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Marc Sun
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9481e9e9f1
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Fix autoround docs (#37675)
* fix * empty |
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Yoni Gozlan
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a245011252
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Add InternVL (2.5 MPO) (#35968)
* initial commit * add convert internvl * add first end-to-end working internvl * nit prompt and image proc * add working chat template * add conversion llama-based models * add tests * pass all tests * fix isort * fix modular after main merge * add video processing for internvl * add support for interlaced images and videos * Remove processing and config from modular, add more tests * add llama model tests * Modify processor for compatibility with refactored got ocr image processor * add comments in processor * Add docs and nits * change video processing to use custom sample_indices_fn * rebase and fix tests * add processor tests * Add changes Raushan review * Use the new attention interface for the vision model * nits * add support for custom video_load_backend * remove mention to InternVLTokenizer * refactor vision model to simplify logic * refactor processor for better readibility * fix copies * fix require av processor test * refactor internVL vision * Update processor and fix processing tests * fix docstring * update convert_weights for internvl3 * change image processor to fast by default * remove do_center_crop=True in convert_weights * force use_cache to True * push_to_hub before reloading * fix internVLVision for larger models * update convert weight for qk norm * fix convert_weights * fix eos_token_id in convert * update docs and integration tests * make modifs after review * fix wrong k_norm and reduce modular * change image_token_index to image_token_id * change checkpoint to OpenGVLab org * last nits * explicitely del self.num_key_value_groups * add extra special tokens |
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Yaswanth Gali
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a2ef3cf537
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Add Janus model (#36053)
* Iterative generation using input embeds * Add Janus model * discard changes * Janus imports * Refactor config and processor * Added Vision tower of Janus * Import Janus Image processor * Vision tower fixes * Refactor code * Added VQ Model * Complete model integration * temp conversion script * processor refactor * Adding files to facilitate pulling * Fixes after debugging * Skip test for these models * Add Janus Model * discard changes * Janus imports * Refactor config and processor * Added Vision tower of Janus * Import Janus Image processor * Vision tower fixes * Refactor code * Added VQ Model * Complete model integration * temp conversion script * processor refactor * Adding files to facilitate pulling * Fixes after debugging * Refactor to Text config * ✨ Added generate function * Saving intermediate convert file. Still need to read configs from the hub and convert them to our format. * Adding version that reads from the JSON files. Still have to tweak some parameters manually. * relative imports * Initial tests * Refactor image processor * Seemingly working version of the conversion script, will need to test further. * Adding command message * Fixing conflicting JanusTextConfig class * Incorporating some of the discussed changes. * Small fix to create dir. * Removing system from JINJA template * Adding draft processor tests * style fixes * Minor fixes and enhancement * added generation config * Initial tests * Small modifications, tests are now passing. * Small changes I noticed while reading code. * more fixes * Added JanusModel class * Small merge adaptations * Small merge adaptations * Image processing tests passing * More tests and fixes * Convert script updated and refactored * Tests and cleanup * make style * Postprocessing for image generation * generate refactor * fixes * - Passing tests that write a part of the model to cpu (e.g. test_cpu_offload) - Passing tests of dispatching SDPA - Only gradient checkpointing tests are left. * Removing temporary code * Changes * Writing change to modular * Added JanusVisionModel. SDPA dispatch tests pass more robustly. Gradient checkpoint tests are next * Gradient checkpoint tests passing * Removing debug code * Major generate refactor 😮💨 * Temp changes for testing * Green quality CI * 2 out of 4 integration tests passing * breadcrumbs * Usage Examples * Regenerate modeling after merge * dirty code * JanusIntegrationTest are passing * breadcrumbs * happy CI * fixes * Changing template * nits * Text generation logits matching original codebase at 100% precision * Remove ./tmp from git tracking * Remove ./tmp from git tracking * Checkpointing changes after reviewing * Fixing code in docstrings * CHanging comments and small bug in convert file * Fixing bug in image_token_id for 7B version * Removing line that was added by both of us * Pushing changes after discussion. Only one left is to change the key mapping for convert file. * Updating module file * New convert file using dict. Tested that it is equivalent to the old one by: - comparing keys in a script - comparing checksums of the output files between version generated with the current convert script and those generated with the old script. This is a more reliable test. * revert changes * mistake * consistency change for CI * make style * doc fixes * more fixes * experimenting with masking out pad token * checkpoint * Batched generation with multi-images working for 1B models. Will test 7B next. * Device fix. * Writing changes to modular, previous ones were written to modeling just for quick testing. * Using passed processor attention mask (only in modeling for now) * Matching performance done in the non-standard way * Working version of batched generation. Will change how some args are passed to make it more similar to language case * More compliant version of the code * Removed duplicated `_prepare_4d_causal_attention_mask_with_cache_position` * Updating modular file, making masked filling with paddings more efficient * Slightly more efficient version * Modifying JanusVisionModel to be a wrapper * Fixing test to comply with new names * Modular overhaul * More refactoring * - Changing JanusVisionModel back - Changing forward pass - Adding boi token to the comparison * - Removing whole context model_ids - Using inherited implementation of prepare_inputs_for_generation * Moving the way boi token is passed to the model * Fixing sdpa test * Minor changes * testing changes * Minor fix * - Adding postprocessing test - checking values of generated image on integration test * changes * Removing pooled attention vision module, fixing convert script as a consequence * More changes * Fixes * Draft after merge * Bug fixes * More bug fix * Fixing docs * Nits * Refactor return dict * Moving image post processing test to main processor post process * Passing guidance_scale as kwarg * make style * 🔥 refactor * make style * Update and green CI * Nits and tests update * up * Added MID block * fix * Dead code * update testcase * update * model_id change * init_weight changes --------- Co-authored-by: hsilva664 <metallic-silver@hotmail.com> |
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DerekLiu35
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9ddcf5fce5
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Update quantization docs (#37439) | ||
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Jinan Zhou
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a91020aed0
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Add TimesFM Time Series Forecasting Model (#34082)
* initial documentation * rename mask to attention_mask * smaller tests * fixup * fix copies * move to time series section * sort docs * isort fix * batch_size is not a configuration * rename to TimesFMModelForPrediction * initial script * add check_outputs * remove dropout_rate * works with torch.Tensor inputs * rename script * fix docstrings * fix freq when window_size is given * add loss * fix _quantile_loss * formatting * fix isort * add weight init * add support for sdpa and flash_attention_2 * fixes for flash_attention * formatting * remove flash_attention * fix tests * fix file name * fix quantile loss * added initial TimesFMModelIntegrationTests * fix formatting * fix import order * fix _quantile_loss * add doc for SDPA * use timesfm 2.0 * bug fix in timesfm decode function. * compare mean forecasts * refactor type hints, use CamelCase * consolidate decode func * more readable code for weight conversion * fix-copies * simpler init * renaem TimesFmMLP * use T5LayerNorm * fix tests * use initializer_range * TimesFmModel instead of TimesFmDecoder * TimesFmPositionalEmbedding takes config for its init * 2.0-500m-pytorch default configs * use TimesFmModel * fix formatting * ignore TimesFmModel for testing * fix docstring * override generate as its not needed * add doc strings * fix logging * add docstrings to output data classes * initial copy from t5 * added config and attention layers * add TimesFMPositionalEmbedding * calcuate scale_factor once * add more configs and TimesFMResidualBlock * fix input_dims * standardize code format with black * remove unneeded modules * TimesFM Model * order of imports * copy from Google official implementation * remove covariate forecasting * Adapting TimesFM to HF format * restructing in progress * adapted to HF convention * timesfm test * the model runs * fixing unit tests * fixing unit tests in progress * add post_init * do not change TimesFMOutput * fixing unit tests * all unit tests passed * remove timesfm_layers * add intermediate_size and initialize with config * initial documentation * rename mask to attention_mask * smaller tests * fixup * fix copies * move to time series section * sort docs * isort fix * batch_size is not a configuration * rename to TimesFMModelForPrediction * initial script * add check_outputs * remove dropout_rate * works with torch.Tensor inputs * rename script * fix docstrings * fix freq when window_size is given * add loss * fix _quantile_loss * formatting * fix isort * add weight init * add support for sdpa and flash_attention_2 * fixes for flash_attention * formatting * remove flash_attention * fix tests * fix file name * fix quantile loss * added initial TimesFMModelIntegrationTests * fix formatting * fix import order * fix _quantile_loss * add doc for SDPA * use timesfm 2.0 * bug fix in timesfm decode function. * compare mean forecasts * refactor type hints, use CamelCase * consolidate decode func * more readable code for weight conversion * fix-copies * simpler init * renaem TimesFmMLP * use T5LayerNorm * fix tests * use initializer_range * TimesFmModel instead of TimesFmDecoder * TimesFmPositionalEmbedding takes config for its init * 2.0-500m-pytorch default configs * use TimesFmModel * fix formatting * ignore TimesFmModel for testing * fix docstring * override generate as its not needed * add doc strings * fix logging * add docstrings to output data classes * add _CHECKPOINT_FOR_DOC * fix comments * Revert "fix comments" This reverts commit |
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Merve Noyan
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c08997c52e
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VDR task guide (#37485)
* VDR task guide * Add to toctree * Update docs/source/en/tasks/visual_document_retrieval.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/tasks/visual_document_retrieval.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/tasks/visual_document_retrieval.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/tasks/visual_document_retrieval.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/tasks/visual_document_retrieval.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/tasks/visual_document_retrieval.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/tasks/visual_document_retrieval.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/tasks/visual_document_retrieval.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/tasks/visual_document_retrieval.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/tasks/visual_document_retrieval.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> --------- Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> |
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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
|
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 |