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- 03 Aug, 2020 10 commits
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Victor SANH authored
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Kevin Canwen Xu authored
* Remove out-dated BERT tips * Update modeling_outputs.py * Update bert.rst * Update bert.rst
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Sylvain Gugger authored
* Init work on pipelines doc * Work in progress * Work in progress * Doc pipelines * Rm unwanted default * Apply suggestions from code review Lysandre comments Co-authored-by:
Lysandre Debut <lysandre@huggingface.co> Co-authored-by:
Lysandre Debut <lysandre@huggingface.co>
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Sam Shleifer authored
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Maurice Gonzenbach authored
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Suraj Patil authored
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Jay Mody authored
* Adds train_batch_size, eval_batch_size, and n_gpu to to_sanitized_dict() output * Update wandb config logging to use to_sanitized_dict * removed n_gpu from sanitized dict * fix quality check errors
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Julien Plu authored
* Fix TF Serving when output_hidden_states and output_attentions are True * Add tests for saved model creation + bug fix for multiple choices models * remove unused import * Fix the input for several layers * Fix test * Fix conflict printing * Apply style * Fix XLM and Flaubert for TensorFlow * Apply style * Fix TF check version * Apply style * Trigger CI
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Teven authored
* Fixed empty asserts * black-reformatted stragglers in templates * More code quality checks * Update src/transformers/convert_marian_to_pytorch.py Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Update src/transformers/convert_marian_to_pytorch.py Co-authored-by:
Sam Shleifer <sshleifer@gmail.com> * removed unused line as per @sshleifer Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by:
Sam Shleifer <sshleifer@gmail.com>
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Martin Müller authored
* Add script to convert tf2.x checkpoint to pytorch The script converts the newer TF2.x checkpoints (as published on their official GitHub: https://github.com/tensorflow/models/tree/master/official/nlp/bert) to Pytorch. * rename file in order to stay consistent with naming convention
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- 02 Aug, 2020 1 commit
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Philip May authored
- remove duplicate doc-entry for tokenize_chinese_chars - add doc for strip_accents and wordpieces_prefix
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- 01 Aug, 2020 2 commits
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Stas Bekman authored
Co-authored-by:Sam Shleifer <sshleifer@gmail.com>
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Faiaz Rahman authored
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- 31 Jul, 2020 10 commits
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Joe Davison authored
* Add bart-large-mnli-yahoo-answers model card * Add examples * Add widget example * Rm bart tag Co-authored-by:
Julien Chaumond <chaumond@gmail.com> Co-authored-by:
Julien Chaumond <chaumond@gmail.com>
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Sylvain Gugger authored
* Use return_dict=True in all tests * Formatting
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Sylvain Gugger authored
* Harmonize both Trainers API * Fix test * main_prcess -> process_zero
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Mehrdad Farahani authored
* readme m3hrdadfi/albert-fa-base-v2 model_card readme for m3hrdadfi/albert-fa-base-v2 * Update model_cards/m3hrdadfi/albert-fa-base-v2/README.md Co-authored-by:Julien Chaumond <chaumond@gmail.com>
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Suraj Patil authored
* add parse_dict to parse arguments from dict * add unit test for parse_dict
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Paul O'Leary McCann authored
* Replace mecab-python3 with fugashi This replaces mecab-python3 with fugashi for Japanese tokenization. I am the maintainer of both projects. Both projects are MeCab wrappers, so the underlying C++ code is the same. fugashi is the newer wrapper and doesn't use SWIG, so for basic use of the MeCab API it's easier to use. This code insures the use of a version of ipadic installed via pip, which should make versioning and tracking down issues easier. fugashi has wheels for Windows, OSX, and Linux, which will help with issues with installing old versions of mecab-python3 on Windows. Compared to mecab-python3, because fugashi doesn't use SWIG, it doesn't require a C++ runtime to be installed on Windows. In adding this change I removed some code dealing with `cursor`, `token_start`, and `token_end` variables. These variables didn't seem to be used for anything, it is unclear to me why they were there. I ran the tests and they passed, though I couldn't figure out how to run the slow tests (`--runslow` gave an error) and didn't try testing with Tensorflow. * Style fix * Remove unused variable Forgot to delete this... * Adapt doc with install instructions * Fix typo Co-authored-by:
sgugger <sylvain.gugger@gmail.com> Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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Stas Bekman authored
* enable easy checkout switch allow having multiple repository checkouts and not needing to remember to rerun 'pip install -e .[dev]' when switching between checkouts and running tests. * make isort happy * examples needs one too
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kolk authored
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Prajjwal Bhargava authored
* fixed type; add Pytorch Native CUDA AMP support * reverted commit on modeling_utils * confirming to HF black formatting rule * changed bool value of _use_apex * scaler support for gradient clipping * fix inplace operation of clip_grad_norm * removed not while version comparison
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Funtowicz Morgan authored
* Add onnxruntime transformers optimization support Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Added Optimization section in ONNX/ONNXRuntime documentation. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Improve note reference Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Fixing imports order. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Add warning about different level of optimization between torch and tf export. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Address @LysandreJik wording suggestion Co-authored-by:
Lysandre Debut <lysandre@huggingface.co> * Address @LysandreJik wording suggestion Co-authored-by:
Lysandre Debut <lysandre@huggingface.co> * Always optimize model before quantization for maximum performances. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Address comments on the documentation. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Improve TensorFlow optimization message as suggested by @yufenglee Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Removed --optimize parameter Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Warn the user about current quantization limitation when model is larger than 2GB. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Trigger CI for last check * Small change in print for the optimization section. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> Co-authored-by:
Lysandre Debut <lysandre@huggingface.co>
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- 30 Jul, 2020 10 commits
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Stas Bekman authored
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Stas Bekman authored
* 2 small typos * more typos * correct path
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Sylvain Gugger authored
* Start doc tokenizers * Tokenizer documentation * Start doc tokenizers * Tokenizer documentation * Formatting after rebase * Formatting after merge * Update docs/source/main_classes/tokenizer.rst Co-authored-by:
Lysandre Debut <lysandre@huggingface.co> * Address comment * Update src/transformers/tokenization_utils_base.py Co-authored-by:
Thomas Wolf <thomwolf@users.noreply.github.com> * Address Thom's comments Co-authored-by:
Lysandre Debut <lysandre@huggingface.co> Co-authored-by:
Thomas Wolf <thomwolf@users.noreply.github.com>
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guillaume-be authored
* initial commit for pipeline implementation Addition of input processing and history concatenation * Conversation pipeline tested and working for single & multiple conversation inputs * Added docstrings for dialogue pipeline * Addition of dialogue pipeline integration tests * Delete test_t5.py * Fixed max code length * Updated styling * Fixed test broken by formatting tools * Removed unused import * Added unit test for DialoguePipeline * Fixed Tensorflow compatibility * Fixed multi-framework support using framework flag * - Fixed docstring - Added `min_length_for_response` as an initialization parameter - Renamed `*args` to `conversations`, `conversations` being a `Conversation` or a `List[Conversation]` - Updated truncation to truncate entire segments of conversations, instead of cutting in the middle of a user/bot input * - renamed pipeline name from dialogue to conversational - removed hardcoded default value of 1000 and use config.max_length instead - added `append_response` and `set_history` method to the Conversation class to avoid direct fields mutation - fixed bug in history truncation method * - Updated ConversationalPipeline to accept only active conversations (otherwise a ValueError is raised) * - Simplified input tensor conversion * - Updated attention_mask value for Tensorflow compatibility * - Updated last dialogue reference to conversational & fixed integration tests * Fixed conflict with master * Updates following review comments * Updated formatting * Added Conversation and ConversationalPipeline to the library __init__, addition of docstrings for Conversation, added both to the docs * Update src/transformers/pipelines.py Updated docsting following review Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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Lysandre Debut authored
* Fix GPU test * Remove legacy constructor
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Sylvain Gugger authored
* Switch from return_tuple to return_dict * Fix test * [WIP] Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleC… (#5614) * Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleChoice} models and tests * AutoModels Tiny tweaks * Style * Final changes before merge * Re-order for simpler review * Final fixes * Addressing @sgugger's comments * Test MultipleChoice * Rework TF trainer (#6038) * Fully rework training/prediction loops * fix method name * Fix variable name * Fix property name * Fix scope * Fix method name * Fix tuple index * Fix tuple index * Fix indentation * Fix variable name * fix eval before log * Add drop remainder for test dataset * Fix step number + fix logging datetime * fix eval loss value * use global step instead of step + fix logging at step 0 * Fix logging datetime * Fix global_step usage * Fix breaking loop + logging datetime * Fix step in prediction loop * Fix step breaking * Fix train/test loops * Force TF at least 2.2 for the trainer * Use assert_cardinality to facilitate the dataset size computation * Log steps per epoch * Make tfds compliant with TPU * Make tfds compliant with TPU * Use TF dataset enumerate instead of the Python one * revert previous commit * Fix data_dir * Apply style * rebase on master * Address Sylvain's comments * Address Sylvain's and Lysandre comments * Trigger CI * Remove unused import * Switch from return_tuple to return_dict * Fix test * Add recent model Co-authored-by:Lysandre Debut <lysandre@huggingface.co> Co-authored-by:
Julien Plu <plu.julien@gmail.com>
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Sylvain Gugger authored
* Clean up TFTrainer * Add import * Fix conflicts
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Oren Amsalem authored
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Oren Amsalem authored
a = tokenizer.encode("we got a <extra_id_99>", return_tensors='pt',add_special_tokens=True) print(a) >tensor([[ 62, 530, 3, 9, 32000]]) a = tokenizer.encode("we got a <extra_id_100>", return_tensors='pt',add_special_tokens=True) print(a) >tensor([[ 62, 530, 3, 9, 3, 2, 25666, 834, 23, 26, 834, 2915, 3155]]) -
Stas Bekman authored
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- 29 Jul, 2020 7 commits
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Julien Plu authored
* Fully rework training/prediction loops * fix method name * Fix variable name * Fix property name * Fix scope * Fix method name * Fix tuple index * Fix tuple index * Fix indentation * Fix variable name * fix eval before log * Add drop remainder for test dataset * Fix step number + fix logging datetime * fix eval loss value * use global step instead of step + fix logging at step 0 * Fix logging datetime * Fix global_step usage * Fix breaking loop + logging datetime * Fix step in prediction loop * Fix step breaking * Fix train/test loops * Force TF at least 2.2 for the trainer * Use assert_cardinality to facilitate the dataset size computation * Log steps per epoch * Make tfds compliant with TPU * Make tfds compliant with TPU * Use TF dataset enumerate instead of the Python one * revert previous commit * Fix data_dir * Apply style * rebase on master * Address Sylvain's comments * Address Sylvain's and Lysandre comments * Trigger CI * Remove unused import
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Lysandre Debut authored
* Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleChoice} models and tests * AutoModels Tiny tweaks * Style * Final changes before merge * Re-order for simpler review * Final fixes * Addressing @sgugger's comments * Test MultipleChoice -
Sylvain Gugger authored
* Use google style to document properties * Update src/transformers/configuration_utils.py Co-authored-by:
Lysandre Debut <lysandre@huggingface.co> Co-authored-by:
Lysandre Debut <lysandre@huggingface.co>
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Julien Plu authored
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Lysandre Debut authored
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Timo Moeller authored
* Add xlm-r QA model card * Add tags
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Funtowicz Morgan authored
* Added capability to quantize a model while exporting through ONNX. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> We do not support multiple extensions Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Reformat files Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * More quality Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Ensure test_generate_identified_name compares the same object types Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Added documentation everywhere on ONNX exporter Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Use pathlib.Path instead of plain-old string Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Use f-string everywhere Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Use the correct parameters for black formatting Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Use Python 3 super() style. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Use packaging.version to ensure installed onnxruntime version match requirements Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Fixing imports sorting order. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Missing raise(s) Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Added quantization documentation Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Fix some spelling. Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co> * Fix bad list header format Signed-off-by:
Morgan Funtowicz <morgan@huggingface.co>
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