- 18 Apr, 2024 2 commits
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tomeras91 authored
* Add jamba arch * apply "make fix-copies" changes * fix link to model in JambaConfig docstring * Add n_ctx in modeling file because repo-consistency wants that * Add jamba to flash attention and sdpa documentation * mamba dt_proj quant fix now works for LoRA as well * override test_left_padding_compatibility and use a more permissive tolerance. left padding numerical difference are accentuated by mamba layers * add jamba to tokenization auto * fix comments of shape (PR #24 in the model page: https://huggingface.co/ai21labs/Jamba-v0.1/discussions/24) * simple PR fixes * remove unnecessary kwargs from JambaAttentionDecoderLayer and JambaMambaDecoderLayer * remove the LoRA hack for the mamba dt_proj bias. It was solved in huggingface/peft#1530 (https://github.com/huggingface/peft/pull/1530) * Add copied comment on JambaMLP (it's the same as MixtralMLP) * remove padding_mask warnings. It's not supported anymore * fix docstring. Float instead of int * A few more minor PR fixes * (1) lowercase names for mamba layernorms (2) remove _apply_inner_layernorms and do it directly in the forward pass * Return None attention weights from mamba layers. Append to all attentions only if not None. * remove some leftover jamba archive lists * Better separation between expert vs non-expert layers. non-expert layers return None as router_logits, and it is not concatenated to all_router_logits returned from JambaModel * no need to take router_logits at config.expert_layer_offset anymore. result.router_logits now holds results only for expert layers * Add Jamba paper on READMEs * (1) rename n_ctx -> max_position_embeddings (2) don't use it in the modeling file since it's not needed (set it as an exception to check_config_attributes) * Add copied from comment * remove the code path for apply_inner_layernorms=False. Jamba always has the inner mamba layernorms * clearer docstring for _convert_to_standard_cache * style fixes * Change calc_logits_for_entire_prompt (bool) to num_logits_to_keep (int). Adapt assisted decoding code tp use it. Also small change in low memory beam search decoding path to support this new int value in model_inputs * rename test so it still overrides what its meant to override * draft * oups * nit * remove more complexe logic * fix names used in config * fix fix fix * style * fix some more failing tests * generate did not init the cache
馃檭 * more small nits * typo * config.mamba_expand * config.hidden_size for the intermediate size of the mamba shapes * fix init of pkv with torch.tensor() * empty tensor * fix some init issues * stupid changes required by generate because it does not even support it's own DynamicCache class * more fixes * fix general assisted gen cache_position bug * tests passing * Add offsets and periods as SPECIAL_CASES_TO_ALLOW in check_config_attributes.py * fix reorder_cache to reorder mamba states and override some more functions in HybridMambaAttentionDynamicCache * no need to override test_past_key_values_format() and _check_past_key_values_for_generate() in tests anymore * fix docstrings and typehints for past_key_values * style fixes * fix docs * change typehint due to copy from Mixtral * forgot import * import order * Add configuration_jamba and modeling_jamba to not_doctested because the model is too big to download (in docstring of JambaForCausalLM.forward) * Add integration test with tiny tandom Jamba model on hub * fix flash attention cache shapes * bring back forgotten hidden states * rename HybridMambaAttentionDynamicCache.seqlen_offset to has_previous_state (and make bool) and bugfix - it should be set to True after a finished forward pass of the entire model * align integration test after modeling fixes * bugfix - mamba can use precomputed states only of forward pass is on a single token * bugfix - mamba can use precomputed states only if they match the batch size * typo * remove making _prepare_4d_causal_attention_mask a leaf function * stop using past_seq_len.get_seq_length(). Use cache positions instead. Adjust test (test_decoder_model_past_with_large_inputs) accordingly --------- Co-authored-by:Arthur Zucker <arthur.zucker@gmail.com> Co-authored-by:
Joao Gante <joao@huggingface.co>
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Alexander Visheratin authored
* Added flash attention 2. * Fixes. * Fix inheritance. * Fixed init. * Remove stuff. * Added documentation. * Add FA2 to M2M100 documentation. * Add test. * Fixed documentation. * Update src/transformers/models/m2m_100/modeling_m2m_100.py Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * Update docs/source/en/model_doc/nllb.md Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Fixed variable name. --------- Co-authored-by:
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- 17 Apr, 2024 3 commits
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Shane A authored
* Add OLMo using add-new-model-like with Llama * Fix incorrect tokenizer for OLMo * Copy-paste relevant OLMo methods and their imports * Add OLMo config * Modify OLMo config to follow HF conventions * Remove unneeded Llama code from OLMo model * Add ability for OLMo model to output attentions * Add OLMoPreTrainedModel and OLMoModel * Add OLMoForCausalLM * Minor fixes to OLMo model for style and missing functions * Implement OLMo tokenizer * Implement OLMo to HF conversion script * Add tests for OLMo model * Add tests for OLMo fast tokenizer * Add auto-generated dummy objects * Remove unimplemented OLMo classes from auto and init classes and re-format * Add README and associated auto-generated files * Use OLMo names for common properties * Run make fixup * Remove `|` from OLMo typing * Remove unneeded tokenization_olmo.py * Revert model, config and converter to add-new-model-like Llama * Move logic for adding bos/eos token into GPTNeoxTokenizerFast * Change OLMoConfig defaults to match OLMo-7B * Use GPTNeoXToknizerFast in OLMo tokenizer tests * Modify auto-generated OLMoModelTests to work for OLMo * Add non-parametric layer norm OLMoLayerNorm * Update weight conversion script for OLMo * Fix __init__ and auto structure for OLMo * Fix errors from make fixup * Remove OLMoTokenizerFast from documentation * Add missing 'Copied from' for OLMoModel._update_causal_mask * Run make fix-copies * Rearrange string replacements in OLMoForCausalLM Copied from * Move OLMo and Llama CausalLM.forward example into global constants * Fix OLMO_GENERATION_EXAMPLE doc string typo * Add option for qkv clipping to OLMo * Rearrange OLMoConfig kwargs in convert_olmo_weights_to_hf * Add clip_qkv to OLMoConfig in convert_olmo_weights_to_hf * Fix OLMo tokenization bug using conversion script * Keep model in full precision after conversion * Do not add eos token automatically * Update references to OLMo model in HF Hub * Do not add eos token during encoding by default * Fix Llama generation example * Run make fixup * OLMo 7B integration test fix * Remove unneeded special case for OLMoConfig * OLMo 7B Twin 2T integration test fix * Fix test_model_7b_greedy_generation * Remove test_compile_static_cache * Fix OLMo and Llama generation example * Run make fixup * Revert "OLMo 7B integration test fix" This reverts commit 4df56a4b150681bfa559846f40e9b7b7f97d7908. * Revert "OLMo 7B Twin 2T integration test fix" This reverts commit 9ff65a4a294ace89ab047b793ca55e623a9ceefc. * Ungate 7B integration tests and fix greedy generation test * Add retries for flaky test_eager_matches_sdpa_generate * Fix output of doc example for OLMoForCausalLM.forward * Downsize OLMo doc test for OLMoForCausalLM.forward to 1B model * Try fix incorrect characters in OLMoForCausalLM.forward doct test * Try fix incorrect characters in OLMoForCausalLM.forward doc test using end quotes * Remove pretraining_tp from OLMo config and model * Add missing 'Copied from' instances * Remove unneeded causal_mask from OLMoModel * Revert Llama changes * Ignore copy for OLMoForCausalLM.forward * Change 'OLMo' to 'Olmo' in classes * Move minimal OLMo tokenization tests to model tests * Add missed 'Copied from' for repeat_kv
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st81 authored
* Add create token type ids to CodeGenTokenizer * Fix inconsistent length of token type ids * Format source codes * Fix inconsistent order of methods * Update docstring * add test_tokenizer_integration test * Format source codes * Add `copied from` comment to CodeGenTokenizerFast * Add doc of create_token_type_ids_from_sequences * Make return_token_type_ids False by default * Make test_tokenizer_integration as slow test * Add return_token_type_ids to tokenizer init arg * Add test for tokenizer's init return_token_type_ids * Format source codes
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Utkarsha Gupte authored
* Configuring Translation Pipelines documents update #27753 Configuring Translation Pipelines documents update * Language Format Addition * adding supported list of languages list
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- 16 Apr, 2024 2 commits
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Hafedh authored
* add `push_to_hub` to pipeline * fix docs * format with ruff * update save_pretrained * update save_pretrained * remove unnecessary comment * switch to push_to_hub method in DynamicPipelineTester * remove unused imports * update docs for add_new_pipeline * fix docs for add_new_pipeline * add comment * fix italien docs * changes to token retrieval for pipelines * Update src/transformers/pipelines/base.py Co-authored-by:
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Yih-Dar authored
* fix * update * update * fix --------- Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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- 15 Apr, 2024 4 commits
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Matt authored
Remove incorrect arg in codellama docstring
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Sayak Paul authored
Update recurrent_gemma.md
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amyeroberts authored
* Initial add model additions * Test * All weights loading * Can perform full forward pass * Local and remote the same * Matching local and remote * Fixup * Idefics2Model importable; fixup docstrings * Don't skip by default * Remove deprecated use_resampler arg * Remove self.config * DecoupledLinear takes config * Tidy up * Enable eager attention and tidy up * Most tests passing * Update for batch of processed images * Add image processor * Update doc pages * Update conversion script * Remove erroneous breakpoint * Remove accidendtal spelling change * Update to reflect changes on hub - make generate work * Fix up * Image processor tests * Update tests * Add a processor * Add a processor * Update convert script * Update modeling file - remove fixmes * Bug fix * Add processing test * Use processor * Fix up * Update src/transformers/models/idefics2/modeling_idefics2.py Co-authored-by:
Victor SANH <victorsanh@gmail.com> * Update src/transformers/models/idefics2/modeling_idefics2.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Remove qk_layer_norm and freeze_layers functionality * Fix * Remove freeze_layer options from config * Sync with upstream main * Fix attention shapes siglip * Remove Llava-next refs - TO REBASE * Use AutoModel for text model * Add comment to explain vision embeddings * Fix issue with tie_word_embeddings * Address review comments * Fix and fix up * Chat templates for idefics * Fix copies * Fix * Add layer norms to FA2 * Fix tests * Apply suggestions from code review Co-authored-by:
Pablo Montalvo <39954772+molbap@users.noreply.github.com> Co-authored-by:
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Yih-Dar authored
* fix * fix --------- Co-authored-by:
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- 11 Apr, 2024 2 commits
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lewtun authored
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Eduardo Pacheco authored
* Fixed typo when converting weigths to GroundingDINO vision backbone * Final modifications on modeling * Removed unnecessary class * Fixed convert structure * Added image processing * make fixup partially completed * Now text_backbone_config has its own class * Modified convert script * Removed unnecessary config attribute * Added new function to generate sub sentence mask * Renamed parameters with gamma in the name as it's currently not allowed * Removed tokenization and image_processing scripts since we'll map from existing models * Fixed some issues with configuration * Just some modifications on conversion script * Other modifications * Copied deformable detr * First commit * Added bert to model * Bert validated * Created Text and Fusion layers for Encoder * Adapted Encoder layer * Fixed typos * Adjusted Encoder * Converted encoder to hf * Modified Decoder Layer * Modified main decoder class * Removed copy comments * Fixed forward from GroundingDINOModel and GroundingDINODecoder * Added all necessary layers, configurations and forward logic up to GroundingDINOModel * Added all layers to convertion * Fixed outputs for GroundingDINOModel and GroundingDINOForObjectDetection * Fixed mask input to encoders and fixed nn.MultiheadAttention batch first and attn output * Fixed forward from GroundingDINOTextEnhancerLayer * Fixed output bug with GroundingDINODeformableLayer * Fixed bugs that prevent GroundingDINOForObjectDetection to run forward method * Fixed attentions to be passed correctly * Passing temperature arg when creating Sine position embedding * Removed copy comments * Added temperature argument for position embedding * Fixed typo when converting weigths to GroundingDINO vision backbone * Final modifications on modeling * Removed unnecessary class * Fixed convert structure * Added image processing * make fixup partially completed * Now text_backbone_config has its own class * Modified convert script * Removed unnecessary config attribute * Added new function to generate sub sentence mask * Renamed parameters with gamma in the name as it's currently not allowed * Removed tokenization and image_processing scripts since we'll map from existing models * Fixed some issues with configuration * Just some modifications on conversion script * Other modifications * Fix style * Improve fixup * Improve conversion script * Improve conversion script * Add GroundingDINOProcessor * More improvements * Return token type ids * something * Fix more tests * More improvements * More cleanup * More improvements * Fixed tests, improved modeling and config * More improvements and fixing tests * Improved tests and modeling * Improved tests and added image processor * Improved tests inference * More improvements * More test improvements * Fixed last test * Improved docstrings and comments * Fix style * Update src/transformers/models/grounding_dino/modeling_grounding_dino.py Co-authored-by:
Rafael Padilla <31217453+rafaelpadilla@users.noreply.github.com> * Update src/transformers/models/grounding_dino/modeling_grounding_dino.py Co-authored-by:
NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/grounding_dino/modeling_grounding_dino.py Co-authored-by:
Sangbum Daniel Choi <34004152+SangbumChoi@users.noreply.github.com> * Update src/transformers/models/grounding_dino/modeling_grounding_dino.py Co-authored-by:
Tianqi Xu <40522713+dandansamax@users.noreply.github.com> * Update docs/source/en/model_doc/grounding-dino.md Co-authored-by:
Niels <niels.rogge1@gmail.com> Co-authored-by:
Eduardo Pacheco <eduardo.pacheco@limehome.com> Co-authored-by:
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- 10 Apr, 2024 2 commits
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Arthur authored
* Fork. * RecurrentGemma initial commit. * Updating __init__.py. * Minor modification to how we initialize the cache. Changing how the config specifies the architecture. * Reformat code to 4 spaces. Fixed a few typos. * Fixed the forward pass. Still unclear on the cache? * Fixed the RecurrentGemmaForCausalLM * Minor comment that we might not need attention_mask and output_attention arguments. * Now cache should work as well. * Adding a temporary example to check whether the model generation works. * Adding the tests and updating imports. * Adding the example file missing in the previous commit. * First working example. * Removing .gitignore and reverting parts of __init__. * Re-add .gitignore. * Addressing comments for configuration. * Move mask creation to `_prepare_inputs_for_generation`. * First try at integration tests: 1. AttributeError: 'GriffinCausalLMOutput' object has no attribute 'attentions'. 2. `cache_position` not passed * Transfoering between machines. * Running normal tests. * Minor fix. * More fixes. * Addressing more comments. * Minor fixes. * first stab at cleanup * more refactoring * fix copies and else * renaming and get init to work * fix causal mask creation * update * nit * fix a hell lot of things * updates * update conversion script * make all keys importable * nits * add auto mappings * properly convert ffw_up and down * add scaling * fix generations * for recurrent dtype * update * fix going beyong window * fixup * add missing files * current updates to remove last einops * finish modeling refactor * TADA * fix compile * fix most failing testt ? ? * update tests * refactor and update * update * nits, fixup and update tests * more fixup * nits * fix imports * test format * fixups * nits * tuple typing * fix code quality * add model card * fix doc * skip most generation tests * nits * style * doc fixes * fix pr and check_copies? * last nit * oupsy * Apply suggestions from code review Co-authored-by:
Lysandre Debut <hi@lysand.re> * update * Update src/transformers/models/recurrent_gemma/convert_recurrent_gemma_to_hf.py Co-authored-by:
Aleksandar Botev <botev@google.com> Co-authored-by:
Leonard Berrada <lberrada@users.noreply.github.com> Co-authored-by:
anushanf <anushanf@google.com> Co-authored-by:
botev <botevmg@gmail.com> Co-authored-by:
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NielsRogge authored
* Improve docs * Add more tips
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- 09 Apr, 2024 2 commits
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Steven Liu authored
fixes
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NielsRogge authored
* Undo * Use tokenizer * Undo data collator
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- 08 Apr, 2024 1 commit
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Utkarsha Gupte authored
* ImportError: Trainer with PyTorch requires accelerate>=0.20.1 Fix Adding the evaluate and accelerate installs at the beginning of the cell to fix the issue * ImportError Fix: Trainer with PyTorch requires accelerate>=0.20.1 * Import Error Fix * Update installation.md * Update quicktour.md * rollback other lang changes * Update _config.py * updates for other languages * fixing error * Tutorial Update * Update tokenization_utils_base.py * Just use an optimizer string to pass the doctest? --------- Co-authored-by:Matt <rocketknight1@gmail.com>
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- 05 Apr, 2024 1 commit
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NielsRogge authored
* Add image processor to trainer * Replace tokenizer=image_processor everywhere
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- 03 Apr, 2024 1 commit
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Steven Liu authored
new audio file
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- 02 Apr, 2024 3 commits
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Michael authored
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Yoach Lacombe authored
* add FA2 to o.g Musicgen * make style * add FA2 support to Musicgen Melody * add generation FA2 tests to o.g Musicgen * make style and fix copies * add Musicgen to FA2 docs + deprecate list * add sdpa supports to Musicgen's * make style and fix copies * refactor attention implementation arguments * add Copied from to sdpa tests * add copied form in sdpa tests melody * add copied for FA2 generation tests * add FA2 inference copied from * make style
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Steven Liu authored
* update * feedback
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- 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:
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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:
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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: -
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:
steven <steven.bucaillle@gmail.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:
Matthew Douglas <38992547+matthewdouglas@users.noreply.github.com> * Update src/transformers/training_args.py Co-authored-by:
hiyouga <hiyouga@users.noreply.github.com> Co-authored-by:
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