- 30 Mar, 2024 1 commit
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Bo Zheng authored
* Update qwen2_moe.md * update link of blogpost. * fixup --------- Co-authored-by:bozheng-hit <dsoul0621@gmail.com>
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- 29 Mar, 2024 1 commit
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fzyzcjy authored
* with with * style
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- 28 Mar, 2024 4 commits
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MariaHei authored
Trainer with PyTorch now requires accelerate to be installed. Partly resolves huggingface/transformers#29174
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Aymeric Roucher authored
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Fanli Lin authored
fix typo
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Eduardo Pacheco authored
* First commit to add flash attention 2 for GPT-2 * more improvements * Make GPT2 pass tests and fixed Decison Transformers copies * Fixed missing arg * fix copies * Added expected speedup * Update src/transformers/models/gpt2/modeling_gpt2.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/gpt2/modeling_gpt2.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/gpt2/modeling_gpt2.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Added test * Fixed attn attribute * Update docs/source/en/model_doc/gpt2.md Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update docs/source/en/model_doc/gpt2.md Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update Decision transformer attentions * More updates * Passing tests * Fix copies * Fix copies part 2 * Decision transformer updates * Update src/transformers/models/gpt2/modeling_gpt2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Fix copies * Decision transformer not supporting flash attn * Addressed comments * Addressed comments * Addressed comments --------- Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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- 27 Mar, 2024 1 commit
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Bo Zheng authored
* add support for qwen2 MoE models * update docs * add support for qwen2 MoE models * update docs * update model name & test * update readme * update class names & readme & model_doc of Qwen2MoE. * update architecture name * fix qwen2_moe tests * use Qwen2Tokenizer instead of Qwen2MoeTokenizer * update modeling_qwen2_moe.py * fix model architecture * fix qwen2_moe tests * use Qwen2Tokenizer instead of Qwen2MoeTokenizer * update modeling_qwen2_moe.py * fix model architecture * fix style * fix test when there are sparse and non sparse layers * fixup * Update README.md Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * fixup * fixup * add archive back * add support for qwen2 MoE models * update docs * update model name & test * update readme * update class names & readme & model_doc of Qwen2MoE. * update architecture name * fix qwen2_moe tests * use Qwen2Tokenizer instead of Qwen2MoeTokenizer * update modeling_qwen2_moe.py * fix model architecture * fixup * fix qwen2_moe tests * use Qwen2Tokenizer instead of Qwen2MoeTokenizer * fix style * fix test when there are sparse and non sparse layers * fixup * add archive back * fix integration test * fixup --------- Co-authored-by:
bozheng-hit <dsoul0621@gmail.com> Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com>
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- 26 Mar, 2024 2 commits
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Michael authored
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Merve Noyan authored
Update image_feature_extraction.md
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- 25 Mar, 2024 1 commit
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Johannes Kolbe authored
Co-authored-by:Johannes <johannes.kolbe@tech.better.team>
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- 24 Mar, 2024 1 commit
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gamepad_coder authored
* model_summary.md - Add link to Harvard's Annotated Transformer. * model_summary.md - slight wording change + capitalize name of the paper * model_summary.md - moves the Annotated Transformer link in a praenthesis next to the link to the original paper (great idea, stevhliu!) * model_summary.md - moves the Annotated Transformer link in a praenthesis next to the link to the original paper (commit pt. 2, accidentally removed "has" in pt. 1)
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- 23 Mar, 2024 1 commit
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Billy Cao authored
Fix typo for llava next docs
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- 21 Mar, 2024 1 commit
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Michael authored
[docs] Remove redundant and from custom_tools.md
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- 20 Mar, 2024 2 commits
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NielsRogge authored
* First draft * Fix tests, add docs * Improve docstrings * Fix test * Address comments * Address comments * Remove vocab_size attribute * Remove batch_size * Address comment * Add image processor tests * Support fx * Update docstring * Add support for 34b * Convert 34b model * Add integration tests * Update checkpoints * Convert vicuna-13b, remove doc tests * Remove script * Remove file * Address comments * Improve docstrings * Deprecate vocab_size * Remove aspect_ratio_setting * Address comments * Update READMEs * Add tips about chat templates * Fix tests * Deprecate vocab_size safely * Update tests --------- Co-authored-by:Amy Roberts <22614925+amyeroberts@users.noreply.github.com>
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amyeroberts authored
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- 19 Mar, 2024 2 commits
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StevenBucaille authored
* Added SuperPoint docs * Added tests * Removed commented part * Commit to create and fix add_superpoint branch with a new branch * Fixed dummy_pt_objects * Committed missing files * Fixed README.md * Apply suggestions from code review Fixed small changes Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Moved ImagePointDescriptionOutput from modeling_outputs.py to modeling_superpoint.py * Removed AutoModelForKeypointDetection and related stuff * Fixed inconsistencies in image_processing_superpoint.py * Moved infer_on_model logic simply in test_inference * Fixed bugs, added labels to forward method with checks whether it is properly a None value, also added tests about this logic in test_modeling_superpoint.py * Added tests to SuperPointImageProcessor to ensure that images are properly converted to grayscale * Removed remaining mentions of MODEL_FOR_KEYPOINT_DETECTION_MAPPING * Apply suggestions from code review Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Fixed from (w, h) to (h, w) as input for tests * Removed unnecessary condition * Moved last_hidden_state to be the first returned * Moved last_hidden_state to be the first returned (bis) * Moved last_hidden_state to be the first returned (ter) * Switched image_width and image_height in tests to match recent changes * Added config as first SuperPointConvBlock init argument * Reordered README's after merge * Added missing first config argument to SuperPointConvBlock instantiations * Removed formatting error * Added SuperPoint to README's de, pt-br, ru, te and vi * Checked out README_fr.md * Fixed README_fr.md * Test fix README_fr.md * Test fix README_fr.md * Last make fix-copies ! * Updated checkpoint path * Removed unused SuperPoint doc * Added missing image * Update src/transformers/models/superpoint/modeling_superpoint.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Removed unnecessary import * Update src/transformers/models/superpoint/modeling_superpoint.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Added SuperPoint to _toctree.yml --------- Co-authored-by:
steven <steven.bucaillle@gmail.com> Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by:
Steven Bucaille <steven.bucaille@buawei.com>
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Younes Belkada authored
* add galore v1 * add import * add tests and doc * fix doctest * forward contrib credits from discussions * forward contrib credits from discussions * Apply suggestions from code review Co-authored-by:
Zach Mueller <muellerzr@gmail.com> * fix failing tests' * switch to `optim_target_modules` and clarify docs * more clarification * enhance lookup logic * update a test to add peak memory * add regex, all-linear and single string support * add layer-wise optimization through DummyOptimizers and LRSchedulers * forward contrib credits from discussions and original idea * add a section about DDP not supported in layerwise * Update src/transformers/trainer.py Co-authored-by:
Zach Mueller <muellerzr@gmail.com> * fix self * check only if layer_wise * Update src/transformers/training_args.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * oops * make use of intervals * clarify comment * add matching tests * GaLoRe -> GaLore * move to `get_scheduler` * add note on docs * add a warning * adapt a bit the docs * update docstring * support original API * Update docs/source/en/trainer.md * slightly refactor * Update docs/source/en/trainer.md Co-authored-by:
Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com> * Update src/transformers/training_args.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * fix args parsing and add tests * remove warning for regex * fix type hint * add note about extra args * make `is_regex` return optional --------- Co-authored-by: Maxime <maximegmd @users.noreply.github.com> Co-authored-by: Wing Lian <winglian @users.noreply.github.com> Co-authored-by:
Zach Mueller <muellerzr@gmail.com> Co-authored-by:
hiyouga <hiyouga@users.noreply.github.com> Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by:
Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com>
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- 18 Mar, 2024 2 commits
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Abubakar Abid authored
* Update pipeline_tutorial.md to include gradio * Update pipeline_tutorial.md * Update docs/source/en/pipeline_tutorial.md Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/pipeline_tutorial.md Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/pipeline_tutorial.md Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/pipeline_tutorial.md Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update pipeline_tutorial.md * Update docs/source/en/pipeline_tutorial.md Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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Yoach Lacombe authored
* first modeling code * make repository * still WIP * update model * add tests * add latest change * clean docstrings and copied from * update docstrings md and readme * correct chroma function * correct copied from and remove unreleated test * add doc to toctree * correct imports * add convert script to notdoctested * Add suggestion from Sanchit Co-authored-by:
Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * correct get_uncoditional_inputs docstrings * modify README according to SANCHIT feedback * add chroma to audio utils * clean librosa and torchaudio hard dependencies * fix FE * refactor audio decoder -> audio encoder for consistency with previous musicgen * refactor conditional -> encoder * modify sampling rate logics * modify license at the beginning * refactor all_self_attns->all_attentions * remove ignore copy from causallm generate * add copied from for from_sub_models * fix make copies * add warning if audio is truncated * add copied from where relevant * remove artefact * fix convert script * fix torchaudio and FE * modify chroma method according to feedback-> better naming * refactor input_values->input_features * refactor input_values->input_features and fix import fe * add input_features to docstrigs * correct inputs_embeds logics * remove dtype conversion * refactor _prepare_conditional_hidden_states_kwargs_for_generation ->_prepare_encoder_hidden_states_kwargs_for_generation * change warning for chroma length * Update src/transformers/models/musicgen_melody/convert_musicgen_melody_transformers.py Co-authored-by:
Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * change way to save wav, using soundfile * correct docs and change to soundfile * fix import * fix init proj layers * remove line breaks from md * fix issue with docstrings * add FE suggestions * improve is in logics and remove useless imports * remove custom from_pretrained * simplify docstring code * add suggestions for modeling tests * make style * update converting script with sanity check * remove encoder attention mask from conditional generation * replace musicgen melody checkpoints with official orga * rename ylacombe->facebook in checkpoints * fix copies * remove unecessary warning * add shape in code docstrings * add files to slow doc tests * fix md bug and add md to not_tested * make fix-copies * fix hidden states test and batching --------- Co-authored-by:
Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
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- 15 Mar, 2024 3 commits
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Aaron Jimenez authored
* add attention to es/ and edit es/_toctree.yml * translate attention.md * fix transformers * fix transformers
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Marc Sun authored
* start integration * fix * add and debug tests * update tests * make pytorch serialization works * compatible with device_map and offload * fix tests * make style * add ref * guard against safetensors * add float8 and style * fix is_serializable * Fix shard_checkpoint compatibility with quanto * more tests * docs * adjust memory * better * style * pass tests * Update src/transformers/modeling_utils.py Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * add is_safe_serialization instead * Update src/transformers/quantizers/quantizer_quanto.py Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * add QbitsTensor tests * fix tests * simplify activation list * Update docs/source/en/quantization.md Co-authored-by:
David Corvoysier <david.corvoysier@gmail.com> * better comment * Update tests/quantization/quanto_integration/test_quanto.py Co-authored-by:
David Corvoysier <david.corvoysier@gmail.com> * Update tests/quantization/quanto_integration/test_quanto.py Co-authored-by:
David Corvoysier <david.corvoysier@gmail.com> * find and fix edge case * Update docs/source/en/quantization.md Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * pass weights_only_kwarg instead * fix shard_checkpoint loading * simplify update_missing_keys * Update tests/quantization/quanto_integration/test_quanto.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * recursion to get all tensors * block serialization * skip serialization tests * fix * change by cuda:0 for now * fix regression * update device_map * fix doc * add noteboon * update torch_dtype * update doc * typo * typo * remove comm --------- Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by:
David Corvoysier <david.corvoysier@gmail.com> Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by:
Younes Belkada <younesbelkada@gmail.com>
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Saurabh Dash authored
* Cohere Model Release (#1) Cohere Model Release * Remove unnecessary files and code (#2) Some cleanup * Delete cohere-model directory (#3) * Make Fix (#5) * Pr fixes (#6) * fixes for pr * pr fixes for the format * pr fixes for the format * src/transformers/models/auto/tokenization_auto.py * Tokenizer test (#8) * tokenizer test * format fix * Adding Docs and other minor changes (#7) * Add modeling tests (#9) * Smol Fix (#11) * tokenization tests are fixed * format fixes * fix pr doc tests * fix pr doc tests * fix pr doc tests * fix pr style check * small changes in cohere.md * FIX: Address final comments for transformers integration (#13) * fix modeling final nits and add proper test file * for now leave empty tests * add integration test * push new test * fix modeling cohere (#14) * Update chat templates to use the new API (#15) --------- Co-authored-by:
ahmetustun <ahmetustun89@gmail.com> Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by:
Matt <Rocketknight1@users.noreply.github.com>
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- 13 Mar, 2024 6 commits
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Aaron Jimenez authored
* remove ChatML link from en/ * remove ChatML link in ja/ * remove ChatML link in zh/
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Nate Cibik authored
* Added pytests for pvt-v2, all passed * Added pvt_v2 to docs/source/end/model_doc * Ran fix-copies and fixup. All checks passed * Added additional ReLU for linear attention mode * pvt_v2_b2_linear converted and working * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * PvT-v2 now works in AutoModel * Reverted batch eval changes for PR * Expanded type support for Pvt-v2 config * Fixed config docstring. Added channels property * Fixed model names in tests * Fixed config backbone compat. Added additional type support for image size in config * Fixed config backbone compat * Allowed for batching of eval metrics * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * Set key and value layers to use separate linear modules. Fixed pruning function * Set AvgPool to 7 * Fixed issue in init * PvT-v2 now works in AutoModel * Successful conversion of pretrained weights for PVT-v2 * Successful conversion of pretrained weights for PVT-v2 models * Added pytests for pvt-v2, all passed * Ran fix-copies and fixup. All checks passed * Added additional ReLU for linear attention mode * pvt_v2_b2_linear converted and working * Allowed for batching of eval metrics * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * Set key and value layers to use separate linear modules. Fixed pruning function * Set AvgPool to 7 * Fixed issue in init * PvT-v2 now works in AutoModel * Successful conversion of pretrained weights for PVT-v2 * Successful conversion of pretrained weights for PVT-v2 models * Added pytests for pvt-v2, all passed * Ran fix-copies and fixup. All checks passed * Added additional ReLU for linear attention mode * pvt_v2_b2_linear converted and working * Reverted batch eval changes for PR * Updated index.md * Expanded type support for Pvt-v2 config * Fixed config docstring. Added channels property * Fixed model names in tests * Fixed config backbone compat * Ran fix-copies * Fixed PvtV2Backbone tests * Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py * Fixed backbone stuff and fixed tests: all passing * Ran make fixup * Made modifications for code checks * Remove ONNX config from configuration_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Use explicit image size dict in test_modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Make image_size optional in test_modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Remove _ntuple use in modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Remove reference to fp16_enabled * Model modules now take config as first argument even when not used * Replaced abbreviations for "SR" and "AP" with explicit "spatialreduction" and "averagepooling" * All LayerNorm now instantiates with config.layer_norm_eps * Added docstring for depth-wise conv layer * PvtV2Config now only takes Union[int, Tuple[int, int]] for image size * Refactored PVTv2 in prep for gradient checkpointing * Gradient checkpointing ready to test * Removed override of _set_gradient_checkpointing * Cleaned out old code * Applied code fixup * Applied code fixup * Began debug of pvt_v2 tests * Leave handling of num_labels to base pretrained config class * Deactivated gradient checkpointing tests until it is fixed * Removed PvtV2ImageProcessor which duped PvtImageProcessor * Allowed for batching of eval metrics * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * Set key and value layers to use separate linear modules. Fixed pruning function * Set AvgPool to 7 * Fixed issue in init * PvT-v2 now works in AutoModel * Successful conversion of pretrained weights for PVT-v2 * Successful conversion of pretrained weights for PVT-v2 models * Added pytests for pvt-v2, all passed * Added pvt_v2 to docs/source/end/model_doc * Ran fix-copies and fixup. All checks passed * Added additional ReLU for linear attention mode * pvt_v2_b2_linear converted and working * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * PvT-v2 now works in AutoModel * Reverted batch eval changes for PR * Expanded type support for Pvt-v2 config * Fixed config docstring. Added channels property * Fixed model names in tests * Fixed config backbone compat. Added additional type support for image size in config * Fixed config backbone compat * Allowed for batching of eval metrics * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * Set key and value layers to use separate linear modules. Fixed pruning function * Set AvgPool to 7 * Fixed issue in init * PvT-v2 now works in AutoModel * Successful conversion of pretrained weights for PVT-v2 * Successful conversion of pretrained weights for PVT-v2 models * Added pytests for pvt-v2, all passed * Ran fix-copies and fixup. All checks passed * Added additional ReLU for linear attention mode * pvt_v2_b2_linear converted and working * Allowed for batching of eval metrics * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * Set key and value layers to use separate linear modules. Fixed pruning function * Set AvgPool to 7 * Fixed issue in init * PvT-v2 now works in AutoModel * Successful conversion of pretrained weights for PVT-v2 * Successful conversion of pretrained weights for PVT-v2 models * Added pytests for pvt-v2, all passed * Ran fix-copies and fixup. All checks passed * Added additional ReLU for linear attention mode * pvt_v2_b2_linear converted and working * Reverted batch eval changes for PR * Expanded type support for Pvt-v2 config * Fixed config docstring. Added channels property * Fixed model names in tests * Fixed config backbone compat * Ran fix-copies * Fixed PvtV2Backbone tests * Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py * Fixed backbone stuff and fixed tests: all passing * Ran make fixup * Made modifications for code checks * Remove ONNX config from configuration_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Use explicit image size dict in test_modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Make image_size optional in test_modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Remove _ntuple use in modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Remove reference to fp16_enabled * Model modules now take config as first argument even when not used * Replaced abbreviations for "SR" and "AP" with explicit "spatialreduction" and "averagepooling" * All LayerNorm now instantiates with config.layer_norm_eps * Added docstring for depth-wise conv layer * PvtV2Config now only takes Union[int, Tuple[int, int]] for image size * Refactored PVTv2 in prep for gradient checkpointing * Gradient checkpointing ready to test * Removed override of _set_gradient_checkpointing * Cleaned out old code * Applied code fixup * Applied code fixup * Allowed for batching of eval metrics * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * PvT-v2 now works in AutoModel * Ran fix-copies and fixup. All checks passed * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * PvT-v2 now works in AutoModel * Reverted batch eval changes for PR * Fixed config docstring. Added channels property * Fixed config backbone compat * Allowed for batching of eval metrics * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * PvT-v2 now works in AutoModel * Ran fix-copies and fixup. All checks passed * Allowed for batching of eval metrics * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * PvT-v2 now works in AutoModel * Fixed config backbone compat * Ran fix-copies * Began debug of pvt_v2 tests * Leave handling of num_labels to base pretrained config class * Deactivated gradient checkpointing tests until it is fixed * Removed PvtV2ImageProcessor which duped PvtImageProcessor * Fixed issue from rebase * Fixed issue from rebase * Set tests for gradient checkpointing to skip those using reentrant since it isn't supported * Fixed issue from rebase * Fixed issue from rebase * Changed model name in docs * Removed duplicate PvtV2Backbone * Work around type switching issue in tests * Fix model name in config comments * Update docs/source/en/model_doc/pvt_v2.md Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Changed name of variable from 'attn_reduce' to 'sr_type' * Changed name of variable from 'attn_reduce' to 'sr_type' * Changed from using 'sr_type' to 'linear_attention' for clarity * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py Removed old code * Changed from using 'sr_type' to 'linear_attention' for clarity * Fixed Class names to be more descriptive * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py Removed outdated code * Moved paper abstract to single line in pvt_v2.md * Added usage tips to pvt_v2.md * Simplified module inits by passing layer_idx * Fixed typing for hidden_act in PvtV2Config * Removed unusued import * Add pvt_v2 to docs/source/en/_toctree.yml * Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive. * Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive. * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py Move function parameters to single line Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py Update year of copyright to 2024 Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py Make code more explicit Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Updated sr_ratio to be more explicit spatial_reduction_ratio * Removed excess type hints in modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Move params to single line in modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Removed needless comment in modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update copyright date in pvt_v2.md Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Moved params to single line in modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Updated copyright date in configuration_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Cleaned comments in modeling_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Renamed spatial_reduction Conv2D operation * Revert "Update src/transformers/models/pvt_v2/modeling_pvt_v2.py " This reverts commit c4a04416dde8f3475ab405d1feb368600e0f8538. * Updated conversion script to reflect module name change * Deprecated reshape_last_stage option in config * Removed unused imports * Code formatting * Fixed outdated decorators on test_inference_fp16 * Added "Copied from" comments in test_modeling_pvt_v2.py * Fixed import listing * Updated model name * Force empty commit for PR refresh * Fixed linting issue * Removed # Copied from comments * Added PVTv2 to README_fr.md * Ran make fix-copies * Replace all FoamoftheSea hub references with OpenGVLab * Fixed out_indices and out_features logic in configuration_pvt_v2.py * Made ImageNet weight conversion verification optional in convert_pvt_v2_to_pytorch.py * Ran code fixup * Fixed order of parent classes in PvtV2Config to fix the to_dict method override --------- Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com>
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njackman-2344 authored
* torchscript and trainer md es translation * corrected md es files and even corrected spelling in en md * made es corrections to trainer.md * deleted entrenamiento... title on yml * placed entrenamiento in right place * translated es chat_templating.md w/ yml addition * requested es changes to md and yml * last es changes to md
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Dries Verachtert authored
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Lysandre Debut authored
* Warn against remote tool use * Additional disclaimer * Update docs/source/en/custom_tools.md Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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bytebarde authored
* initial implementation of flash attention for gptj * modify flash attention and overwrite test_flash_attn_2_generate_padding_right * update flash attention support list * remove the copy line in the `CodeGenBlock` * address copy mechanism * Update src/transformers/models/gptj/modeling_gptj.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Add GPTJ attention classes * add expected outputs in the gptj test * Ensure repo consistency with 'make fix-copies' --------- Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com>
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- 12 Mar, 2024 3 commits
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Furkan Akkurt authored
Update quantization.md
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Dries Verachtert authored
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Raushan Turganbay authored
fix fuyu docs
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- 11 Mar, 2024 5 commits
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fzyzcjy authored
* Update add_new_model.md * Update docs/source/en/add_new_model.md Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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Amrit Gupta authored
Fixed broken link for Resources -> Token Classification -> Finetuning BERT for named-entity
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Yitong Huang authored
* add USE_TORCH_XLA env * rename torch_tpu to torch_xla * better is_torch_xla_available; fix some fsdp and performance issues * fix format * fix bug when pjrt_device is cpu * fix bug * fix the deprecation handling --------- Co-authored-by:
anw90 <ang868@gmail.com> Co-authored-by:
wangang.wa <wangang.wa@alibaba-inc.com>
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j-gc authored
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Arthur authored
* post merge update * nit * oups
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- 07 Mar, 2024 1 commit
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Joao Gante authored
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- 06 Mar, 2024 3 commits
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Joao Gante authored
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Younes Belkada authored
* add accelerate docs * Apply suggestions from code review Co-authored-by:
Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com> * Update starcoder2.md * add correct generation --------- Co-authored-by:
Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>
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Younes Belkada authored
* add docs on exllamav2 + AWQ * Update docs/source/en/quantization.md
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