- 18 Jan, 2024 9 commits
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Sanchit Gandhi authored
* move token ids to cpu * check for torch attr
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Sanchit Gandhi authored
* add image processor arg * super * rm args
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Jeremy Fowers authored
* Fix the documentation checkpoint for xlm-roberta-xl * Improve docstring consistency
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Yih-Dar authored
* inside with LoggingLevel * remove is_flaky --------- Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com>
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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:
Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * make position_embeddings_type docstrings clearer * clean converting script * remove function not used * clean modeling file * apply suggestion for test file + add convert script to not_doctested * modify tests according to review - cleaner logic and more tests * Apply nit suggestions from code review Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * add checker of valid position embeddings type * instantiate new layer norm layer with the right eps * fix freeze_feature_encoder since it can be None in some cases * add test same output in convert script * restore wav2vec2conformer and add new model * create processor and FE + clean * add new model code * fix convert script and set default config parameters * correct model id paths * make style * make fix-copies and cleaning files * fix copied from statements * complete .md and fixe copies * clean convert script argument defaults * fix config parameters docstrings * fix config docstring * add copied from and enrich FE tests * fix copied from and repo-consistency * add autotokenizer * make test input length shorter and change docstring code * fix docstrings and copied from * add add_adapter to ASR training example * make testing of adapters more robust * adapt to multi adapter layers * refactor input_values->input_features and remove w2v2-bert feature extractor * remove pretraining model * remove depreciated features and useless lines * add copied from and ignore statements to modeling tests * remove pretraining model #2 * change import in convert script * change default in convert script * update readme and remove useless line * Update tests/models/wav2vec2_bert/test_processor_wav2vec2_bert.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * refactor BERT to Bert for consistency * remove useless ignore copy statement * add persistent to buffer in rotary * add eps in LayerNorm init and remove copied from * add adapter activation parameters and add copied from statements * Fix copied statements and add unitest.skip reasons * add copied statement in test_processor * refactor processor * make style * replace numpy random by torch rand * remove expected output CTC * improve converting script with processor class * Apply suggestions from code review Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * remove gumbel class * remove tests related to previously deleted class * Update src/transformers/models/wav2vec2_bert/configuration_wav2vec2_bert.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * correct typos * remove uused parameters * update processor to takes both text and audio * update checkpoints * update expected output and add ctc expected output * add label_attention_mask * replace pt with np in processor tests * fix typo * revert to behaviour with labels_attention_mask --------- Co-authored-by:
Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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hugo-syn authored
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Arthur authored
* fix * last attempt * current work * fix forward compatibility * save all special tokens * current state * revert additional changes * updates * remove tokenizer.model * add a test and the fix * nit * revert one more break * fix typefield issue * quality * more tests * fix fields for FC * more nits? * new additional changes * how * some updates * the fix * where do we stand * nits * nits * revert unrelated changes * nits nits nits * styling * don't break llama just yet * revert llama changes * safe arg check * fixup * Add a test for T5 * Necessary changes * Tests passing, added tokens need to not be normalized. If the added tokens are normalized, it will the stripping which seems to be unwanted for a normal functioning * Add even more tests, when normalization is set to True (which does not work
😓 ) * Add even more tests, when normalization is set to True (which does not work😓 ) * Update to main * nits * fmt * more and more test * comments * revert change as tests are failing * make the test more readble * nits * refactor the test * nit * updates * simplify * style * style * style convert slow * Update src/transformers/convert_slow_tokenizer.py -
Yih-Dar authored
* fix * fix * fix --------- Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com>
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Yih-Dar authored
* save processor * Update tests/models/auto/test_processor_auto.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update tests/test_processing_common.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix --------- Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com> Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com>
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- 17 Jan, 2024 7 commits
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Ahmed Elnaggar authored
Fix sparse_step = 1 I case sparse_step = 1, the current code will not work.
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Lucas Thompson authored
I want to train dinov2 with bf16 but I get the following error in https://github.com/huggingface/transformers/blob/bc72b4e2cdcbc80d5f56731f35dbc9c18b4c8de6/src/transformers/models/dinov2/modeling_dinov2.py#L635: ``` RuntimeError: Input type (float) and bias type (c10::BFloat16) should be the same ``` Since the input dtype is torch.float32, the parameter dtype has to be torch.float32... @LZHgrla and I checked the code of clip vision encoder and found there is an automatic dtype transformation (https://github.com/huggingface/transformers/blob/bc72b4e2cdcbc80d5f56731f35dbc9c18b4c8de6/src/transformers/models/clip/modeling_clip.py#L181-L182). So I add similar automatic dtype transformation to modeling_dinov2.py.
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fxmarty authored
* skip bf16 test if not supported by device * fix * fix bis * use is_torch_bf16_available_on_device * use is_torch_fp16_available_on_device * fix & use public llama * use 1b model * fix flacky test --------- Co-authored-by:
Your Name <you@example.com>
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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:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * update test and copied from * fix style * update qwen2 tokenization and tests * Update tokenization_qwen2.py * delete the copied from after property * fix style * update tests * update tests * add copied from * fix bugs * update doc * add warning for sliding window attention * update qwen2 tokenization * fix style * Update src/transformers/models/qwen2/modeling_qwen2.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix tokenizer fast --------- Co-authored-by:
Ren Xuancheng <jklj077@users.noreply.github.com> Co-authored-by:
renxuancheng.rxc <renxuancheng.rxc@alibaba-inc.com> Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com>
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Gustavo de Rosa authored
* fix(phi): Phi does not use softmax_scale in Flash-Attention. * chore(docs): Update Phi docs.
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fxmarty authored
* torch.fx: add pkv, llama, sdpa support * Update src/transformers/models/opt/modeling_opt.py * remove spaces * trigger ci * use explicit variable names
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Patrick von Platen authored
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- 16 Jan, 2024 10 commits
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Joao Gante authored
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inisis authored
* modify check_if_model_is_supported to return bool * add is_model_supported and have check_if_model_is_supported use that * Update src/transformers/utils/fx.py Fantastic Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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fxmarty authored
* clearer error for sdpa * better message
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Arthur authored
[`SpeechT5Tokenization`] Add copied from and fix the `convert_tokens_to_string` to match the fast decoding scheme (#28522) * Add copied from and fix the `convert_tokens_to_string` to match the fast decoding scheme * fixup * add a small test * style test file * nites
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Arthur authored
* cleanup * add a test * update the test * style * revert part that allows to pickle the tokenizer
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Arthur authored
* fix adding special tokens when the token is already there. * add a test * add a test * nit * fix the test: make sure the order is preserved * Update tests/test_tokenization_common.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com>
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Nima Yaqmuri authored
* Fix bug in SpeechT5 speech decoder prenet's forward method - Removed redundant `repeat` operation on speaker_embeddings in the forward method. This line was erroneously duplicating the embeddings, leading to incorrect input size for concatenation and performance issues. - Maintained original functionality of the method, ensuring the integrity of the speech decoder prenet's forward pass remains intact. - This change resolves a critical bug affecting the model's performance in handling speaker embeddings. * Refactor SpeechT5 text to speech integration tests - Updated SpeechT5ForTextToSpeechIntegrationTests to accommodate the variability in sequence lengths due to dropout in the speech decoder pre-net. This change ensures that our tests are robust against random variations in generated speech, enhancing the reliability of our test suite. - Removed hardcoded dimensions in test assertions. Replaced with dynamic checks based on model configuration and seed settings, ensuring tests remain valid across different runs and configurations. - Added new test cases to thoroughly validate the shapes of generated spectrograms and waveforms. These tests leverage seed settings to ensure consistent and predictable behavior in testing, addressing potential issues in speech generation and vocoder processing. - Fixed existing test cases where incorrect assumptions about output shapes led to potential errors. * Fix bug in SpeechT5 speech decoder prenet's forward method - Removed redundant `repeat` operation on speaker_embeddings in the forward method. This line was erroneously duplicating the embeddings, leading to incorrect input size for concatenation and performance issues. - Maintained original functionality of the method, ensuring the integrity of the speech decoder prenet's forward pass remains intact. - This change resolves a critical bug affecting the model's performance in handling speaker embeddings. * Refactor SpeechT5 text to speech integration tests - Updated SpeechT5ForTextToSpeechIntegrationTests to accommodate the variability in sequence lengths due to dropout in the speech decoder pre-net. This change ensures that our tests are robust against random variations in generated speech, enhancing the reliability of our test suite. - Removed hardcoded dimensions in test assertions. Replaced with dynamic checks based on model configuration and seed settings, ensuring tests remain valid across different runs and configurations. - Added new test cases to thoroughly validate the shapes of generated spectrograms and waveforms. These tests leverage seed settings to ensure consistent and predictable behavior in testing, addressing potential issues in speech generation and vocoder processing. - Fixed existing test cases where incorrect assumptions about output shapes led to potential errors. * Enhance handling of speaker embeddings in SpeechT5 - Refined the generate and generate_speech functions in the SpeechT5 class to robustly handle two scenarios for speaker embeddings: matching the batch size (one embedding per sample) and one-to-many (a single embedding for all samples in the batch). - The update includes logic to repeat the speaker embedding when a single embedding is provided for multiple samples, and a ValueError is raised for any mismatched dimensions. - Also added corresponding test cases to validate both scenarios, ensuring complete coverage and functionality for diverse speaker embedding situations. * Improve Test Robustness with Randomized Speaker Embeddings
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fxmarty authored
* fix mismatching behavior in from_pretrained with/without accelerate * meaningful refactor * remove added space * add test * fix model on the hub * comment * use tiny model * style
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Hamza FILALI authored
* Improving Training Performance and Scaling documentation by adding PEFT techniques to suggestions to reduce memory requirements for training * Update docs/source/en/perf_train_gpu_one.md Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> --------- Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
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regisss authored
* Remove `task` arg in `load_dataset` in image-classification example * Manage case where "train" is not in dataset * Add new args to manage image and label column names * Similar to audio-classification example * Fix README * Update tests
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- 15 Jan, 2024 13 commits
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amyeroberts authored
Add back in wrapper for safe importing
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Timothy Cronin authored
* improve dev setup comments and hints * fix tests for new dev setup hints
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Boris Dayma authored
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Joao Gante authored
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Matt authored
* Add a use_safetensors arg to TFPreTrainedModel.from_pretrained() * One more catch! * One more one more catch
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Rishit Ratna authored
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Marc Sun authored
* fix test * reduce length * smaller model
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thedamnedrhino authored
* added args to the pipeline * added test * more sensical tests * fixup * docs * typo ; * docs * made changes to support named args * fixed test * docs update * styles * docs * docs
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yuanwu2017 authored
* Add the XPU check for pipeline mode When setting xpu device for pipeline, It needs to use is_torch_xpu_available to load ipex and determine whether the device is available. Signed-off-by:
yuanwu <yuan.wu@intel.com> * Don't move model to device when hf_device_map isn't None 1. Don't move model to device when hf_device_map is not None 2. The device string maybe includes the device index, so use 'in'instead of equal Signed-off-by:
yuanwu <yuan.wu@intel.com> * Raise the error when xpu is not available Signed-off-by:
yuanwu <yuan.wu@intel.com> * Update src/transformers/pipelines/base.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/pipelines/base.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Modify the error message Signed-off-by:
yuanwu <yuan.wu@intel.com> * Change message format. Signed-off-by:
yuanwu <yuan.wu@intel.com> --------- Signed-off-by:
yuanwu <yuan.wu@intel.com> Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com>
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Younes Belkada authored
* v1 tags * remove unneeded conversion * v2 * rm unneeded warning * add more utility methods * Update src/transformers/utils/hub.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/utils/hub.py Co-authored-by:
Lucain <lucainp@gmail.com> * Update src/transformers/utils/hub.py Co-authored-by:
Lucain <lucainp@gmail.com> * more enhancements * oops * merge tags * clean up * revert unneeded change * add extensive docs * more docs * more kwargs * add test * oops * fix test * Update src/transformers/modeling_utils.py Co-authored-by:
Omar Sanseviero <osanseviero@gmail.com> * Update src/transformers/utils/hub.py Co-authored-by:
Lucain <lucainp@gmail.com> * Update src/transformers/modeling_utils.py * Update src/transformers/trainer.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/modeling_utils.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * add more conditions * more logic --------- Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by:
Lucain <lucainp@gmail.com> Co-authored-by:
Omar Sanseviero <osanseviero@gmail.com>
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Yih-Dar authored
* fix * fix --------- Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com>
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Tom Aarsen authored
Update warning, a word was missing
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Francisco Kurucz authored
Fix URL to Ai Sweden Models reference and model loading
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- 13 Jan, 2024 1 commit
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Joao Gante authored
* fix candidate device * this line shouldn't have been in
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