- 05 Mar, 2024 1 commit
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Arthur authored
* initial-commit * start cleaning * small nits * small nits * current updates * add kernels * small refactoring little step * add comments * styling * nit * nits * Style * Small changes * Push dummy mambda simple slow * nit * Use original names * Use original names and remove norm * Updates for inference params * Style nd updates * nits * Match logits * Add a test * Add expected generated text * nits doc, imports and styling * style * oups * dont install kernels, invite users to install the required kernels * let use use the original packages * styling * nits * fix some copieds * update doc * fix-copies * styling done * nits * fix import check * run but wrong cuda ress * mamba CUDA works :) * fix the fast path * config naming nits * conversion script is not required at this stage * finish fixing the fast path: generation make sense now! * nit * Let's start working on the CIs * style * better style * more nits * test nit * quick fix for now * nits * nit * nit * nit * nits * update test rest * fixup * update test * nit * some fixes * nits * update test values * fix styling * nit * support peft * integrations tests require torchg * also add slow markers * styling * chose forward wisely * nits * update tests * fix gradient checkpointing * fixup * nit * fix doc * check copies * fix the docstring * fix some more tests * style * fix beam search * add init schene * update * nit * fix * fixup the doc * fix the doc * fixup * tentative update but slow is no longer good * nit * should we always use float32? * nits * revert wrong changes * res in float32 * cleanup * skip fmt for now * update generation values * update test values running original model * fixup * update tests + rename inference_params to cache_params + make sure training does not use cache_params * small nits * more nits * fix final CIs * style * nit doc * I hope final doc nits * nit * 馃珷 * final touch! * fix torch import * Apply suggestions from code review Co-authored-by:
Lysandre Debut <hi@lysand.re> * Apply suggestions from code review * fix fix and fix * fix base model prefix! * nit * Update src/transformers/models/mamba/__init__.py * Update docs/source/en/model_doc/mamba.md Co-authored-by:
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- 04 Mar, 2024 2 commits
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NielsRogge authored
* First draft * More improvements * More improvements * More fixes * Fix copies * More improvements * More fixes * More improvements * Convert checkpoint * More improvements, set up tests * Fix more tests * Add UdopModel * More improvements * Fix equivalence test * More fixes * Redesign model * Extend conversion script * Use real inputs for conversion script * Add image processor * Improve conversion script * Add UdopTokenizer * Add fast tokenizer * Add converter * Update README's * Add processor * Add fully fledged tokenizer * Add fast tokenizer * Use processor in conversion script * Add tokenizer tests * Fix one more test * Fix more tests * Fix tokenizer tests * Enable fast tokenizer tests * Fix more tests * Fix additional_special_tokens of fast tokenizer * Fix tokenizer tests * Fix more tests * Fix equivalence test * Rename image to pixel_values * Rename seg_data to bbox * More renamings * Remove vis_special_token * More improvements * Add docs * Fix copied from * Update slow tokenizer * Update fast tokenizer design * Make text input optional * Add first draft of processor tests * Fix more processor tests * Fix decoder_start_token_id * Fix test_initialization * Add integration test * More improvements * Improve processor, add test * Add more copied from * Add more copied from * Add more copied from * Add more copied from * Remove print statement * Update README and auto mapping * Delete files * Delete another file * Remove code * Fix test * Fix docs * Remove asserts * Add doc tests * Include UDOP in exotic model tests * Add expected tesseract decodings * Add sentencepiece * Use same design as T5 * Add UdopEncoderModel * Add UdopEncoderModel to tests * More fixes * Fix fast tokenizer * Fix one more test * Remove parallelisable attribute * Fix copies * Remove legacy file * Copy from T5Tokenizer * Fix rebase * More fixes, copy from T5 * More fixes * Fix init * Use ArthurZ/udop for tests * Make all model tests pass * Remove UdopForConditionalGeneration from auto mapping * Fix more tests * fixups * more fixups * fix the tokenizers * remove un-necessary changes * nits * nits * replace truncate_sequences_boxes with truncate_sequences for fix-copies * nit current path * add a test for input ids * ids that we should get taken from c9f7a32f57440d90ff79890270d376a1cc0acb68 * nits converting * nits * apply ruff * nits * nits * style * fix slow order of addition * fix udop fast range as well * fixup * nits * Add docstrings * Fix gradient checkpointing * Update code examples * Skip tests * Update integration test * Address comment * Make fixup * Remove extra ids from tokenizer * Skip test * Apply suggestions from code review Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update year * Address comment * Address more comments * Address comments * Add copied from * Update CI * Rename script * Update model id * Add AddedToken, skip tests * Update CI * Fix doc tests * Do not use Tesseract for the doc tests * Remove kwargs * Add original inputs * Update casting * Fix doc test * Update question * Update question * Use LayoutLMv3ImageProcessor * Update organization * Improve docs * Update forward signature * Make images optional * Remove deprecated device argument * Add comment, add add_prefix_space * More improvements * Remove kwargs --------- Co-authored-by:
ArthurZucker <arthur.zucker@gmail.com> Co-authored-by:
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NielsRogge authored
* First commit * Improve conversion script * Convert more checkpoints * Update src/transformers/models/sam/convert_sam_original_to_hf_format.py Co-authored-by:
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- 28 Feb, 2024 2 commits
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Marc Sun authored
* [CI] Quantization workflow * build dockerfile * fix dockerfile * update self-cheduled.yml * test build dockerfile on push * fix torch install * udapte to python 3.10 * update aqlm version * uncomment build dockerfile * tests if the scheduler works * fix docker * do not trigger on psuh again * add additional runs * test again * all good * style * Update .github/workflows/self-scheduled.yml Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * test build dockerfile with torch 2.2.0 * fix extra * clean * revert changes * Revert "revert changes" This reverts commit 4cb52b8822da9d1786a821a33e867e4fcc00d8fd. * revert correct change --------- Co-authored-by:
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RaymondLi0 authored
* Copy model * changes * misc * fixes * add embed and residual dropout (#30) * misc * remove rms norm and gated MLP * remove copied mentions where its not a copy anymore * remove unused _shape * copied from mistral instead * fix copies * fix copies * add not doctested * fix * fix copyright * Update docs/source/en/model_doc/starcoder2.md Co-authored-by:
Joel Lamy-Poirier <joel.lamy-poirier@servicenow.com> Co-authored-by:
younesbelkada <younesbelkada@gmail.com> Co-authored-by:
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- 26 Feb, 2024 2 commits
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Eduardo Pacheco authored
* First commit * Improvements * More improvements * Converted original checkpoint to HF checkpoint * Fix style * Fixed forward * More improvements * More improvements * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by:
NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Remove asserts * Remove unnecessary attributes * Changed model name to camel case * Improve forward doc * Improve tests * More improvements * Fix copies * Fix doc * Make SegGptImageProcessor more flexible * Added few-shot test * Fix style * Update READMEs and docs * Update READMEs * Make inputs required * Add SegGptForImageSegmentation * Make tests pass * Rename to out_indicies * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/seggpt/test_modeling_seggpt.py Co-authored-by:
Niels <niels.rogge1@gmail.com> Co-authored-by:
Eduardo Pacheco <eduardo.pacheco@limehome.com> Co-authored-by:
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Merve Noyan authored
* add feature extraction mapping * added prefix * ruff check * minor fix * Update modeling_auto.py * fix typo * remove prefix to make variable public/importable * Update src/transformers/models/auto/modeling_auto.py Co-authored-by:
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- 21 Feb, 2024 1 commit
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Arthur authored
* inital commit * update * update conversion checkpoint * update conversion script * nits * some fixes * nits * merge * fix permute * nits * fix * nits * nits * nits * fix rope * fix both rope * nites * style * make sure flax works * fix flax init code * fix foward * nits * print flax generation out * current code * nits * SIIIIIIIIIIIIIIIIIII * update * add new tokenizer * correct fast tokenizer * fix conversion * more comments * fix modeling and conversion * nits and nits * nits testing * add some tokenization tests * add some edge cases * add slow tests and fix them * fixup * fix copies for modeling * fix copies * add 7B slow tests * fix * fix * fix tests * make tokenizer cis go green * styling * last tokenizer nits * update jax tests * fix flax for 7b * add jit testing
馃 * cleanups * isolated nit, inv_freq for rotary_emb.inv_freq * propagate to jax * Apply suggestions from code review Co-authored-by:Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * adjust test * fix conversion script * change name * correct file names * update conversion script * Fix bos and eos token ids in the model configuration (#3) * update modelling * update conversion script * add static cache for gemma * fix sdpa generate * fix batched * multiple fixes * fix FA2 * final fix * Rename a few missing strings and filenames (#4) * merge with upstream main * fix copies * fix copies * fix fixup * fix fixup * fix * fix * final tests * fix fx gemma tests * fix fx bf16/fp16 tests * update slow fx tests * fx slow tests: one logits, one generation * move jit test standalone * Apply suggestions from code review * nits * tokenizer updates * more tokenization updates: custom GemmaSentencepieceExtrator * style * Update src/transformers/cache_utils.py * Update src/transformers/models/gemma/__init__.py * Update tests/models/gemma/test_modeling_flax_gemma.py * small nits * style * update tokenization test * fix the rotary embedding * with style * fix slow tests * WARNING this commit might be very important for precisions * Update tests/models/gemma/test_modeling_flax_gemma.py * Update src/transformers/models/gemma/configuration_gemma.py Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * Update src/transformers/models/gemma/convert_gemma_weights_to_hf.py Co-authored-by:
馃殌 * update all readmes --------- Co-authored-by:sanchit-gandhi <sanchit@huggingface.co> Co-authored-by:
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- 20 Feb, 2024 1 commit
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Taylor Jackle Spriggs authored
* add support for siglip and chinese-clip model training with contrastive-image-text example * codebase fixups
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- 16 Feb, 2024 2 commits
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Lysandre Debut authored
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Lysandre Debut authored
* Script & Manual edition * Update
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- 14 Feb, 2024 2 commits
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amyeroberts authored
* Enable instantiating model with pretrained backbone weights * Clarify pretrained import * Use load_backbone instead * Add backbone_kwargs to config * Pass kwargs to constructors * Fix up * Input verification * Add tests * Tidy up * Update tests/utils/test_backbone_utils.py Co-authored-by:
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Jonathan Tow authored
* Add `StableLM` * fix(model): re-create from `huggingface-cli add-new-model-like persimmon` * fix: re-add changes to address comments * fix(readme): add links to paper * fix(tokenization_auto): remove `GPTNeoXTokenizerFastFast` ref * fix(tests): re-add `@slow` decorator to integration tests * fix(tests): import slow... * fix(readme_hd): remove whitespace edit * fix(tokenizer): auto tokenizer tuple * skip doctests for `modeling_stablelm`
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- 05 Feb, 2024 1 commit
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amyeroberts authored
* Draft pipeline * Fixup * Fix docstrings * Update doctest * Update pipeline_model_mapping * Update docstring * Update tests * Update src/transformers/pipelines/image_feature_extraction.py Co-authored-by:
Omar Sanseviero <osanseviero@gmail.com> * Fix docstrings - review comments * Remove pipeline mapping for composite vision models * Add to pipeline tests * Remove for flava (multimodal) * safe pil import * Add requirements for pipeline run * Account for super slow efficientnet * Review comments * Fix tests * Swap order of kwargs * Use build_pipeline_init_args * Add back FE pipeline for Vilt * Include image_processor_kwargs in docstring * Mark test as flaky * Update TODO * Update tests/pipelines/test_pipelines_image_feature_extraction.py Co-authored-by:
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- 31 Jan, 2024 3 commits
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Yih-Dar authored
* update / add new workflow files * Add comment * Use env.NUM_SLICES * use scripts * use scripts * use scripts * Fix * using one script * Fix * remove unused file * update * fail-fast: false * remove unused file * fix * fix * use matrix * inputs * style * update * fix * fix * no model name * add doc * allow args * style * pass argument --------- Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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Yih-Dar authored
* avoid using job name * apply to other files --------- Co-authored-by: -
Kian Sierra McGettigan authored
* direct copy from llama work * mistral modules forward pass working * flax mistral forward pass with sliding window * added tests * added layer collection approach * Revert "added layer collection approach" This reverts commit 0e2905bf2236ec323163fc1a9f0c016b21aa8b8f. * Revert "Revert "added layer collection approach"" This reverts commit fb17b6187ac5d16da7c461e1130514dc3d137a43. * fixed attention outputs * added mistral to init and auto * fixed import name * fixed layernorm weight dtype * freeze initialized weights * make sure conversion consideres bfloat16 * added backend * added docstrings * added cache * fixed sliding window causal mask * passes cache tests * passed all tests * applied make style * removed commented out code * applied fix-copies ignored other model changes * applied make fix-copies * removed unused functions * passed generation integration test * slow tests pass * fixed slow tests * changed default dtype from jax.numpy.float32 to float32 for docstring check * skip cache test for FlaxMistralForSequenceClassification since if pad_token_id in input_ids it doesn't score previous input_ids * updated checkpoint since from_pt not included * applied black style * removed unused args * Applied styling and fixup * changed checkpoint for doc back * fixed rf after adding it to hf hub * Add dummy ckpt * applied styling * added tokenizer to new ckpt * fixed slice format * fix init and slice * changed ref for placeholder TODO * added copies from Llama * applied styling * applied fix-copies * fixed docs * update weight dtype reconversion for sharded weights * removed Nullable input ids * Removed unnecessary output attentions in Module * added embedding weight initialziation * removed unused past_key_values * fixed deterministic * Fixed RMS Norm and added copied from * removed input_embeds * applied make style * removed nullable input ids from sequence classification model * added copied from GPTJ * added copied from Llama on FlaxMistralDecoderLayer * added copied from to FlaxMistralPreTrainedModel methods * fix test deprecation warning * freeze gpt neox random_params and fix copies * applied make style * fixed doc issue * skipped docstring test to allign # copied from * applied make style * removed FlaxMistralForSequenceClassification * removed unused padding_idx * removed more sequence classification * removed sequence classification * applied styling and consistency * added copied from in tests * removed sequence classification test logic * applied styling * applied make style * removed freeze and fixed copies * undo test change * changed repeat_kv to tile * fixed to key value groups * updated copyright year * split casual_mask * empty to rerun failed pt_flax_equivalence test FlaxWav2Vec2ModelTest * went back to 2023 for tests_pr_documentation_tests * went back to 2024 * changed tile to repeat * applied make style * empty for retry on Wav2Vec2
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- 30 Jan, 2024 2 commits
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amyeroberts authored
* Enable instantiating model with pretrained backbone weights * Remove doc updates until changes made in modeling code * Use load_backbone instead * Add use_timm_backbone to the model configs * Add missing imports and arguments * Update docstrings * Make sure test is properly configured * Include recent DPT updates
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Poedator authored
* squashed earlier commits for easier rebase * rm rebase leftovers * 4bit save enabled @quantizers * TMP gptq test use exllama * fix AwqConfigTest::test_wrong_backend for A100 * quantizers AWQ fixes * _load_pretrained_model low_cpu_mem_usage branch * quantizers style * remove require_low_cpu_mem_usage attr * rm dtype arg from process_model_before_weight_loading * rm config_origin from Q-config * rm inspect from q_config * fixed docstrings in QuantizationConfigParser * logger.warning fix * mv is_loaded_in_4(8)bit to BnbHFQuantizer * is_accelerate_available error msg fix in quantizer * split is_model_trainable in bnb quantizer class * rm llm_int8_skip_modules as separate var in Q * Q rm todo * fwd ref to HFQuantizer in type hint * rm note re optimum.gptq.GPTQQuantizer * quantization_config in __init__ simplified * replaced NonImplemented with create_quantized_param * rm load_in_4/8_bit deprecation warning * QuantizationConfigParser refactoring * awq-related minor changes * awq-related changes * awq config.modules_to_not_convert * raise error if no q-method in q-config in args * minor cleanup * awq quantizer docstring * combine common parts in bnb process_model_before_weight_loading * revert test_gptq * .process_model_ cleanup * restore dict config warning * removed typevars in quantizers.py * cleanup post-rebase 16 jan * QuantizationConfigParser classmethod refactor * rework of handling of unexpected aux elements of bnb weights * moved q-related stuff from save_pretrained to quantizers * refactor v1 * more changes * fix some tests * remove it from main init * ooops * Apply suggestions from code review Co-authored-by:
Marc Sun <57196510+SunMarc@users.noreply.github.com> * fix awq issues * fix * fix * fix * fix * fix * fix * add docs * Apply suggestions from code review Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by:
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- 29 Jan, 2024 1 commit
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ThibaultLengagne authored
* doc: french README Signed-off-by:
ThibaultLengagne <thibaultl@padok.fr> * doc: Add Depth Anything Signed-off-by:
Sarapuce <alexandreh@padok.fr>
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- 23 Jan, 2024 1 commit
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amyeroberts authored
* Enable instantiating model with pretrained backbone weights * Update tests so backbone checkpoint isn't passed in * Remove doc updates until changes made in modeling code * Clarify pretrained import * Update configs - docs and validation check * Update src/transformers/utils/backbone_utils.py Co-authored-by:
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- 18 Jan, 2024 1 commit
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Yoach Lacombe authored
* first commit * correct default value non causal * update config and modeling code * update converting checkpoint * clean modeling and fix tests * make style * add new config parameters to docstring * fix copied from statements * Apply suggestions from code review Co-authored-by:
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- 17 Jan, 2024 1 commit
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Junyang Lin authored
* add config, modeling, and tokenization * add auto and init * update readme * update readme * update team name * fixup * fixup * update config * update code style * update for fixup * update for fixup * update for fixup * update for testing * update for testing * fix bug for config and tokenization * fix bug for bos token * not doctest * debug tokenizer * not doctest * debug tokenization * debug init for tokenizer * fix style * update init * delete if in token auto * add tokenizer doc * add tokenizer in init * Update dummy_tokenizers_objects.py * update * update * debug * Update tokenization_qwen2.py * debug * Update convert_slow_tokenizer.py * add copies * add copied from and make style * update files map * update test * fix style * fix merge reading and update tests * fix tests * fix tests * fix style * debug a variable in readme * Update src/transformers/models/qwen2/configuration_qwen2.py Co-authored-by:
Ren Xuancheng <jklj077@users.noreply.github.com> Co-authored-by:
renxuancheng.rxc <renxuancheng.rxc@alibaba-inc.com> Co-authored-by:
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- 15 Jan, 2024 1 commit
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Timothy Cronin authored
* improve dev setup comments and hints * fix tests for new dev setup hints
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- 12 Jan, 2024 2 commits
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Matt authored
* Fix TF Regnet docstring * Fix TF Regnet docstring * Make a change to the PyTorch Regnet too to make sure the CI is checking it * Add skips for TFRegnet * Update error message for docstring checker
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Joao Gante authored
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- 11 Jan, 2024 1 commit
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Matt authored
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- 10 Jan, 2024 1 commit
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Sparty authored
* Remove ErnieConfig, ErnieMConfig check_docstrings * Run fix_and_overwrite for ErnieConfig, ErnieMConfig * Replace <fill_type> and <fill_docstring> in configuration_ernie, configuration_ernie_m.py with type and docstring values --------- Co-authored-by:vignesh-raghunathan <vignesh_raghunathan@intuit.com>
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- 08 Jan, 2024 1 commit
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NielsRogge authored
* Add first draft * Use appropriate gelu function * More improvements * More improvements * More improvements * Convert checkpoint * More improvements * Improve docs, remove print statements * More improvements * Add link * remove unused masking function * begin tokenizer * do_lower_case * debug * set split_special_tokens=True * Remove script * Fix style * Fix rebase * Use same design as CLIP * Add fast tokenizer * Add SiglipTokenizer to init, remove extra_ids * Improve conversion script * Use smaller inputs in conversion script * Update conversion script * More improvements * Add processor to conversion script * Add tests * Remove print statements * Add tokenizer tests * Fix more tests * More improvements related to weight initialization * More improvements * Make more tests pass * More improvements * More improvements * Add copied from * Add canonicalize_text * Enable fast tokenizer tests * More improvements * Fix most slow tokenizer tests * Address comments * Fix style * Remove script * Address some comments * Add copied from to tests * Add more copied from * Add more copied from * Add more copied from * Remove is_flax_available * More updates * Address comment * Remove SiglipTokenizerFast for now * Add caching * Remove umt5 test * Add canonicalize_text inside _tokenize, thanks Arthur * Fix image processor tests * Skip tests which are not applicable * Skip test_initialization * More improvements * Compare pixel values * Fix doc tests, add integration test * Add do_normalize * Remove causal mask and leverage ignore copy * Fix attention_mask * Fix remaining tests * Fix dummies * Rename temperature and bias * Address comments * Add copied from to tokenizer tests * Add SiglipVisionModel to auto mapping * Add copied from to image processor tests * Improve doc * Remove SiglipVisionModel from index * Address comments * Improve docs * Simplify config * Add first draft * Make it like mistral * More improvements * Fix attention_mask * Fix output_attentions * Add note in docs * Convert multilingual model * Convert large checkpoint * Convert more checkpoints * Add pipeline support, correct image_mean and image_std * Use padding=max_length by default * Make processor like llava * Add code snippet * Convert more checkpoints * Set keep_punctuation_string=None as in OpenCLIP * Set normalized=False for special tokens * Fix doc test * Update integration test * Add figure * Update organization * Happy new year * Use AutoModel everywhere --------- Co-authored-by:patil-suraj <surajp815@gmail.com>
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- 03 Jan, 2024 1 commit
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Connor Henderson authored
* start - docs, SpeechT5 copy and rename * add relevant code from FastSpeech2 draft, have tests pass * make it an actual conformer, demo ex. * matching inference with original repo, includes debug code * refactor nn.Sequentials, start more desc. var names * more renaming * more renaming * vocoder scratchwork * matching vocoder outputs * hifigan vocoder conversion script * convert model script, rename some config vars * replace postnet with speecht5's implementation * passing common tests, file cleanup * expand testing, add output hidden states and attention * tokenizer + passing tokenizer tests * variety of updates and tests * g2p_en pckg setup * import structure edits * docstrings and cleanup * repo consistency * deps * small cleanup * forward signature param order * address comments except for masks and labels * address comments on attention_mask and labels * address second round of comments * remove old unneeded line * address comments part 1 * address comments pt 2 * rename auto mapping * fixes for failing tests * address comments part 3 (bart-like, train loss) * make style * pass config where possible * add forward method + tests to WithHifiGan model * make style * address arg passing and generate_speech comments * address Arthur comments * address Arthur comments pt2 * lint changes * Sanchit comment * add g2p-en to doctest deps * move up self.encoder * onnx compatible tensor method * fix is symbolic * fix paper url * move models to espnet org * make style * make fix-copies * update docstring * Arthur comments * update docstring w/ new updates * add model architecture images * header size * md wording update * make style
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- 22 Dec, 2023 2 commits
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Yih-Dar authored
* add check_support_list.py * fix * fix --------- Co-authored-by: -
NielsRogge authored
* First draft * More improvements * More improvements * Make all tests pass * Remove script * Update image processor * Address comments * Use new gradient checkpointing method * Convert checkpoints, add integration test * Do not keep aspect ratio for now * Set keep_aspect_ratio=False for beit, add integration test * Remove print statement
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- 18 Dec, 2023 1 commit
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Steven Liu authored
* doc fix friday * deprecated objects * update not_doctested * update toctree
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- 13 Dec, 2023 1 commit
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Younes Belkada authored
* v1 * add-new-model-like * revert * fix forward and conversion script * revert * fix copies * fixup * fix * Update docs/source/en/index.md * Apply suggestions from code review * push * fix * fixes here and there * up * fixup and fix tests * Apply suggestions from code review * add docs * fixup * fixes * docstring * add docstring * fixup * docstring * fixup * nit * docs * more copies * fix copies * nit * update test
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- 11 Dec, 2023 1 commit
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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:
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- 08 Dec, 2023 1 commit
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Yih-Dar authored
* fix * fix --------- Co-authored-by:
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- 07 Dec, 2023 4 commits
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Yih-Dar authored
* fix --------- Co-authored-by: -
Yih-Dar authored
* fix --------- Co-authored-by:
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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:shauray8 <shauray8@users.noreply.github.com> Co-authored-by:
haotian-liu <haotian-liu@users.noreply.github.com> Co-authored-by:
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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:
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