"tests/vscode:/vscode.git/clone" did not exist on "998a90bc7d8b3ecda4b1d0ef17e71afeb6729e2e"
- 11 Dec, 2023 3 commits
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Merve Noyan authored
* Initial commit for AutoBackbone & Backbone * Added timm and clarified out_indices * Swapped the example to out_indices * fix toctree * Update autoclass_tutorial.md * Update backbones.md * Update autoclass_tutorial.md * Add dummy torch input instead * Add dummy torch input * Update autoclass_tutorial.md * Update backbones.md * minor fix * Update docs/source/en/main_classes/backbones.md Co-authored-by:
Maria Khalusova <kafooster@gmail.com> * Update docs/source/en/autoclass_tutorial.md Co-authored-by:
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Arthur authored
* up * up * test * logits ok * up * up * few fixes * conversion script * up * nits * nits * update * nuke * more updates * nites * fix many issues * nit * scatter * nit * nuke megablocks * nits * fix conversion script * nit * remove * nits * nit * update * oupsssss * change * nits device * nits * fixup * update * merge * add copied from * fix the copy mentions * update tests * more fixes * nits * conversion script * add parts of the readme * Update tests/models/mixtral/test_modeling_mixtral.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * new test + conversion script * Apply suggestions from code review Co-authored-by:
Lysandre Debut <hi@lysand.re> * Update docs/source/en/model_doc/mixtral.md Co-authored-by:
younesbelkada <younesbelkada@gmail.com> Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by:
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NielsRogge authored
* More improvements * Improve variable names * Update READMEs, improve docs
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- 08 Dec, 2023 3 commits
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fxmarty authored
* add sdpa * wip * cleaning * add ref * yet more cleaning * and more :) * wip llama * working llama * add output_attentions=True support * bigcode sdpa support * fixes * gpt-bigcode support, require torch>=2.1.1 * add falcon support * fix conflicts falcon * style * fix attention_mask definition * remove output_attentions from attnmaskconverter * support whisper without removing any Copied from statement * fix mbart default to eager renaming * fix typo in falcon * fix is_causal in SDPA * check is_flash_attn_2_available in the models init as well in case the model is not initialized through from_pretrained * add warnings when falling back on the manual implementation * precise doc * wip replace _flash_attn_enabled by config.attn_implementation * fix typo * add tests * style * add a copy.deepcopy on the config in from_pretrained, as we do not want to modify it inplace * obey to config.attn_implementation if a config is passed in from_pretrained * fix is_torch_sdpa_available when torch is not installed * remove dead code * Update src/transformers/modeling_attn_mask_utils.py Co-authored-by:
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Aaron Jimenez authored
* Add pad_truncation to es/_toctree.yml * Add pad_truncation.md to es/ * Translated first two paragraph * Translated paddig argument section * Translated truncation argument section * Translated final paragraphs * Translated table * Fixed typo in the table of en/pad_truncation.md * Run make style | Fix a word * Add Padding (relleno) y el Truncation (truncamiento) in the final paragraphs * Fix relleno and truncamiento words
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Tom Aarsen authored
* Draft version of new KV Caching This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks) / StreamingLLM (https://arxiv.org/abs/2309.17453) to be easily implemented in a third-party or in transformers directly * Address numerous PR suggestions 1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic. 2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls. 3. Remove __bool__ and __getitem__ magic as they're confusing. 4. past_key_values.update(key, value, idx) now returns key, value. 5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR. 6. Separate key_cache and value_cache. Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method. * Implement the SinkCache through backward+forward rotations * Integrate (Sink)Cache with Llama FA2 * Set use_legacy_cache=True as default, allows for test passes * Move from/to_legacy_cache to ...Model class * Undo unnecessary newline change * Remove copy utility from deprecated OpenLlama * Match import style * manual rebase with main * Cache class working with generate (#1) * Draft version of new KV Caching This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks) / StreamingLLM (https://arxiv.org/abs/2309.17453 ) to be easily implemented in a third-party or in transformers directly * Address numerous PR suggestions 1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic. 2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls. 3. Remove __bool__ and __getitem__ magic as they're confusing. 4. past_key_values.update(key, value, idx) now returns key, value. 5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR. 6. Separate key_cache and value_cache. Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method. * Integrate (Sink)Cache with Llama FA2 * Move from/to_legacy_cache to ...Model class * Undo unnecessary newline change * Match import style * working generate * Add tests; Simplify code; Apply changes to Mistral and Persimmon * fix rebase mess * a few more manual fixes * last manual fix * propagate changes to phi * upgrade test * add use_legacy_cache docstring; beef up tests * reintroduce unwanted deletes --------- Co-authored-by:
Tom Aarsen <Cubiegamedev@gmail.com> * move import * add default to model_kwargs.get('use_legacy_cache') * correct failing test * Apply suggestions from code review Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> * apply PR suggestions * fix failing test * Apply suggestions from code review Co-authored-by:
Tom Aarsen <37621491+tomaarsen@users.noreply.github.com> * PR comments * tmp commit * add docstrings * more tests, more docstrings, add to docs * derp * tmp commit * tmp dbg * more dbg * fix beam search bug * cache can be a list of tuples in some models * fix group beam search * all but sinkcache integration tests * fix sink cache and add hard integration test * now also compatible with input_embeds input * PR comments * add Cache support to Phi+FA2 * make fixup --------- Co-authored-by:
Joao Gante <joao@huggingface.co> Co-authored-by:
Joao Gante <joaofranciscocardosogante@gmail.com> Co-authored-by:
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- 07 Dec, 2023 8 commits
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Rockerz authored
* Add models * Add more models * Update docs/source/ja/model_doc/convnextv2.md Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/ja/model_doc/convbert.md Co-authored-by:
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Dina Suehiro Jones authored
Updates the distributed CPU training documentation to add instructions for running on a Kubernetes cluster (#27780) * Updates the Distributed CPU documentation to add a Kubernetes example * Small edits * Fixing link * Adding missing new lines * Minor edits * Update to include Dockerfile snippet * Add comment about tuning env var * Updates based on review comments
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Steven Liu authored
* custom dataset * fix link * feedback
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Joao Gante authored
Co-authored-by: -
Younes Belkada authored
* add model like * logits match * minor fixes * fixes * up * up * add todo * llava processor * keep the processor simple * add conversion script * fixup * fix copies * up * add to index * fix config + logits * fix * refactor * more refactor * more refactor * fix copies * add authors * v1 tests * add `LlavaProcessor` in init * remove unneeded import * up * up * docs * up * fix CI * fix CI * add attention mask in test * make fixup * remove the vision model * that' s the dirty way to do it * nits * nits * updates * add more tests * add input tests * fixup * more styling * nits * updates amd cleanup * fixup the generation expected results * fix the testing script * some cleanup and simplification which does not work yet but almost there! * make correct dispatch operations * vectorize works for batch of images and text * last todos * nits * update test and modeling code * remove useless function for now * fix few issues * fix generation * some nits * add bakllava * nits * remove duplicated code * finis merge * cleanup * missed this line * fill the todos * add left padding offset * add left and rignt padding logic * bool to properly index * make sure * more cleanups * batch is fixed
馃槈 * add correct device for tensor creation * fix some dtype missmatch * ruff * update conversion script * Update src/transformers/__init__.py * fa 2 support + fix conversion script * more * correct reshaping * fix test dict * fix copies by ignoring * fix nit * skip clip vision model * fixup * fixup * LlavaForVisionText2Text -> LlavaForCausalLM * update * fix * raise correct errors * fix * docs * nuke for now * nits here and there * fixup * fix remaining tests * update LlavaForConditionalGeneration instead of CausalLM * fixups * pipeline support * slow and piepline tests * supports batch * nits * cleanup * fix first integration tests * add pad token where needed * correct etsts * fixups * update pipeline testr * fix quality * nits * revert unneeded change * nit * use BatchFeature * from ...feature_extraction_utils import BatchFeature * nits * nits * properly update * more f*** nits * fix copies * comment * keep slow test slow * Update src/transformers/models/llava/processing_llava.py Co-authored-by:Arthur Zucker <arthur.zucker@gmail.com> Co-authored-by:
shauray8 <shauray8@users.noreply.github.com> Co-authored-by:
haotian-liu <haotian-liu@users.noreply.github.com> Co-authored-by:
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Susnato Dhar authored
* add FA and modify doc file * test_flash_attn_2_generate_padding_right test overwritten * comment * modify persimmon modeling file * added speedup graph * more changes
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Nolwenn Bernard authored
* Translation of autoclass tutorial * Update totree to keep only tutorial section * Translate title toctree * Fix typos * Update review comments
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Alex McKinney authored
* Copies `modeling_flax_gpt_neo.py` to start * MLP Block. WIP Attention and Block * Adds Flax implementation of `LlamaMLP` Validated with in-file test. Some slight numeric differences, but assuming it isn't an issue * Adds `FlaxLlamaRMSNorm` layer `flax.linen` includes `RMSNorm` layer but not necessarily in all versions. Hence, we add in-file. * Adds FlaxLlamaAttention Copied from GPT-J as it has efficient caching implementation as well as rotary embeddings. Notice numerically different, but not by a huge amount. Needs investigating * Adds `FlaxLlamaDecoderLayer` numerically inaccurate, debugging.. * debugging rotary mismatch gptj uses interleaved whilst llama uses contiguous i think they match now but still final result is wrong. maybe drop back to just debugging attention layer? * fixes bug with decoder layer still somewhat numerically inaccurate, but close enough for now * adds markers for what to implement next the structure here diverges a lot from the PT version. not a big fan of it, but just get something working for now * implements `FlaxLlamaBlockCollection`] tolerance must be higher than expected, kinda disconcerting * Adds `FlaxLlamaModule` equivalent PyTorch model is `LlamaModel` yay! a language model
馃 * adds `FlaxLlamaForCausalLMModule` equivalent to `LlamaForCausalLM` still missing returning dict or tuple, will add later * start porting pretrained wrappers realised it probably needs return dict as a prereq * cleanup, quality, style * readds `return_dict` and model output named tuples * (tentatively) pretrained wrappers work馃敟 * fixes numerical mismatch in `FlaxLlamaRMSNorm` seems `jax.lax.rsqrt` does not match `torch.sqrt`. manually computing `1 / jax.numpy.sqrt` results in matching values. * [WIP] debugging numerics * numerical match I think issue was accidental change of backend. forcing CPU fixes test. We expect some mismatch on GPU. * adds in model and integration tests for Flax Llama summary of failing: - mul invalid combination of dimensions - one numerical mismatch - bf16 conversion (maybe my local backend issue) - params are not FrozenDict * adds missing TYPE_CHECKING import and `make fixup` * adds back missing docstrings needs review on quality of docstrings, not sure what is required. Furthermore, need to check if `CHECKPOINT_FOR_DOC` is valid. See TODO * commenting out equivalence test as can just use common * debugging * Fixes bug where mask and pos_ids were swapped in pretrained models This results in all tests passing now馃敟 * cleanup of modeling file * cleanup of test file * Resolving simpler review comments * addresses more minor review comments * fixing introduced pytest errors from review * wip additional slow tests * wip tests need to grab a GPU machine to get real logits for comparison otherwise, slow tests should be okay * `make quality`, `make style` * adds slow integration tests - checking logits - checking hidden states - checking generation outputs * `make fix-copies` * fix mangled function following `make fix-copies` * adds missing type checking imports * fixes missing parameter checkpoint warning * more finegrained 'Copied from' tags avoids issue of overwriting `LLAMA_INPUTS_DOCSTRING` * swaps import guards ??? how did these get swapped initially? * removing `inv_freq` again as pytorch version has now removed * attempting to get CI to pass * adds doc entries for llama flax models * fixes typo in __init__.py imports * adds back special equivalence tests these come from the gpt neo flax tests. there is special behaviour for these models that needs to override the common version * overrides tests with dummy to see if CI passes need to fill in these tests later * adds my contribution to docs * `make style; make quality` * replaces random masking with fixed to work with flax version * `make quality; make style` * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by:Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by:
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- 06 Dec, 2023 2 commits
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Rockerz authored
* Add models * Add models and update `_toctree.yml` * Update docs/source/ja/model_doc/chinese_clip.md Co-authored-by:
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Younes Belkada authored
* add flash-attn-2 support for GPT-neo-x * fixup * add comment * revert * fixes * update docs * comment * again * fix copies * add plot + fix copies * Update docs/source/en/model_doc/gpt_neox.md
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- 05 Dec, 2023 4 commits
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Younes Belkada authored
Update quantization.md
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Aaron Jimenez authored
* Copy perplexity.md file to es/ folder * Adding perplexity to es/_toctree.yml * Translate first section * Calculating PPL section translate * Example section translate * fix translate of log-likehood * Fix title translate * Fix \ in second paragraph * Change verosimilitud for log-likelihood * Run 'make style'
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Arindam Jati authored
* patchtsmixer initial commit * x,y->context_values,target_values, unittest addded * cleanup code * minor * return hidden states * model tests, partial integration tests * ettm notebook temporary * minor * config mask bug fix, tests updated * final ETT notebooks * add selfattn * init * added docstrings * PatchTSMixerForPretraining -> PatchTSMixerForMaskPretraining * functionality tests added * add start and input docstrings * docstring edits * testcase edits * minor changes * docstring error fixed * ran make fixup * finalize integration tests and docs * minor * cleaned gitignore * added dataclass decorator, ran black formatter * ran ruff * formatting * add slow decorator * renamed in_Channel to input_size and default to 1 * shorten dataclass names * use smaller model for testing * moved the 3 heads to the modeling file * use scalers instead of revin * support forecast_channel_indices * fix regression scaling * undo reg. scaling * removed unneeded classes * forgot missing * add more layers * add copied positional_encoding * use patchmask from patchtst * removed dependency on layers directory * formatting * set seed * removed unused imports * fixed forward signature test * adding distributional head for PatchTSMixerForecasting * add generate to forecast * testcases for generate * add generate and distributional head for regression * raise Exception for negative values for neg binominal distribution * formatting changes * remove copied from patchtst and add TODO for test passing * make copies * doc edits * minor changes * format issues * minor changes * minor changes * format docstring * change some class names to PatchTSMixer + class name Transpose to PatchTSMixerTranspose GatedAttention to PatchTSMixerGatedAttention * change NormLayer to PatchTSMixerNormLayer * change MLP to PatchTSMixerMLP * change PatchMixer to PatchMixerBlock, FeatureMixer to FeatureMixerBlock * change ChannelFeatureMixer to ChannelFeatureMixerBlock * change PatchMasking to PatchTSMixerMasking * change Patchify to PatchTSMixerPatchify * list to `list` * fix docstrings * formatting * change bs to batch_size, edit forecast_masking * edit random_masking * change variable name and update docstring in PatchTSMixerMasking * change variable name and update docstring in InjectScalerStatistics4D * update forward call in PatchTSMixerTranspose * change variable name and update docstring in PatchTSMixerNormLayer * change variable name and update docstring in PatchTSMixerMLP * change variable name and update docstring in ChannelFeatureMixerBlock * formatting * formatting issues * docstring issue * fixed observed_mask type in docstrings * use FloatTensor type * formatting * fix rescaling issue in forecasting, fixed integration tests * add docstring from decorator * fix docstring * Update README.md Co-authored-by:
NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/patchtsmixer/configuration_patchtsmixer.py Co-authored-by:
Arindam Jati <arindam.jati@ibm.com> Co-authored-by:
vijaye12 <vijaye12@in.ibm.com> Co-authored-by:
Kashif Rasul <kashif.rasul@gmail.com> Co-authored-by:
nnguyen <nnguyen@us.ibm.com> Co-authored-by:
vijaye12 <vijaykr.e@gmail.com> Co-authored-by:
Nam Nguyen <namctin@gmail.com> Co-authored-by:
Wesley Gifford <79663411+wgifford@users.noreply.github.com> Co-authored-by:
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Younes Belkada authored
* v1 fusing modules * add fused mlp support * up * fix CI * block save_pretrained * fixup * small fix * add new condition * add v1 docs * add some comments * style * fix nit * adapt from suggestion * add check * change arg names * change variables name * Update src/transformers/integrations/awq.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * style * split up into 3 different private methods * more conditions * more checks * add fused tests for custom models * fix * fix tests * final update docs * final fixes * fix importlib metadata * Update src/transformers/utils/quantization_config.py Co-authored-by:
Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/utils/quantization_config.py Co-authored-by:
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- 04 Dec, 2023 5 commits
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Rockerz authored
* Create asr.md * Create audio_classification.md * Create document_question_answering.md * Update document_question_answering.md * add * add * ggg * gg * add masked_language_modeling.md * add monocular_depth estimation * new * dd * add * add * cl * add * Add Traslation.md * hgf * Added docs to Toctree file * Update docs/source/ja/tasks/asr.md Co-authored-by:
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jiaqiw09 authored
* translate * update * update --------- Co-authored-by:jiaqiw <wangjiaqi50@huawei.com>
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Yih-Dar authored
* fix * fix * Use TRUST_REMOTE_CODE * fix doc * fix --------- Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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fxmarty authored
* support FA2 * fix typo * fix broken tests * fix more test errors * left/right * fix bug * more test * typo * fix layout flash attention falcon * do not support this case * use allclose instead of equal * fix various bugs with flash attention * bump * fix test * fix mistral * use skiptest instead of return that may be misleading * add fix causal arg flash attention * fix copies * more explicit comment * still use self.is_causal * fix causal argument * comment * fixes * update documentation * add link * wrong test * simplify FA2 RoCm requirements * update opt * make flash_attn_uses_top_left_mask attribute private and precise comment * better error handling * fix copy & mistral * Update src/transformers/modeling_utils.py Co-authored-by:
Felix Marty <felix@hf.co> Co-authored-by:
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Sanchit Gandhi authored
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- 01 Dec, 2023 1 commit
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Nolwenn Bernard authored
* partial traduction of installation * Finish translation of installation * Update installation.mdx * Rename installation.mdx to installation.md * Typos * Update docs/source/fr/installation.md Co-authored-by:
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- 30 Nov, 2023 1 commit
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Yoach Lacombe authored
* add working convertion script * first non-working version of modeling code * update modeling code (working) * make style * make fix-copies * add config docstrings * add config to ignore docstrings formatage due to unconventional markdown * fix copies * fix generation num_return_sequences * enrich docs * add and fix tests beside integration tests * update integration tests * update repo id * add tie weights and make style * correct naming in .md * fix imports and so on * correct docstrings * fix fp16 speech forward * fix speechencoder attention * make style * fix copied from * rename SeamlessM4Tv2-v2 to SeamlessM4Tv2 * Apply suggestions on configuration Co-authored-by:
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- 29 Nov, 2023 1 commit
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Kashif Rasul authored
* add distribution head to forecasting * formatting * Add generate function for forecasting * Add generate function to prediction task * formatting * use argsort * add past_observed_mask ordering * fix arguments * docs * add back test_model_outputs_equivalence test * formatting * cleanup * formatting * use ACT2CLS * formatting * fix add_start_docstrings decorator * add distribution head and generate function to regression task add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput, PatchTSTForRegressionOutput. * add distribution head and generate function to regression task add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput, PatchTSTForRegressionOutput. * fix typos * add forecast_masking * fixed tests * use set_seed * fix doc test * formatting * Update docs/source/en/model_doc/patchtst.md Co-authored-by:
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- 28 Nov, 2023 3 commits
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Steven Liu authored
* first draft * benchmarks * feedback
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Tom Aarsen authored
~transformer. -> ~transformers.
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Juarez Bochi authored
* Add madlad-400 models * Add madlad-400 to the doc table * Update docs/source/en/model_doc/madlad-400.md Co-authored-by:
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- 27 Nov, 2023 5 commits
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Rockerz authored
* Add `model_docs` * Add * Update Model adoc * Update docs/source/ja/model_doc/bark.md Co-authored-by:
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jiaqiw09 authored
* translate work * update * update * update [[autodoc]] * Update callback.md --------- Co-authored-by: -
Matt authored
* Update default ChatML template * Update docs/warnings * Update docs/source/en/chat_templating.md Co-authored-by:
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Peter Pan authored
* docs: replace torch.distributed.run by torchrun `transformers` now officially support pytorch >= 1.10. The entrypoint `torchrun`` is present from 1.10 onwards. Signed-off-by:
Peter Pan <Peter.Pan@daocloud.io> * Update src/transformers/trainer.py with @ArthurZucker's suggestion Co-authored-by:
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Lysandre Debut authored
Reorder
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- 24 Nov, 2023 4 commits
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fxmarty authored
* reflect RoCm support in the documentation * Update docs/source/en/main_classes/trainer.md Co-authored-by:
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Anirudh Haritas Murali authored
Change "convert predictions to logits" to "convert logits to predictions" to fix semantic error in the evaluation section. Logits need to be converted to predictions to evaluate the accuracy, not the other way round
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yoinked authored
* Update musicgen.md please make it less hidden * Add cleaner formatting
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Yih-Dar authored
* fix * fix * trigger * Apply suggestions from code review Co-authored-by:
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