GitLab

* Fixing #13381

* Enabling automatic LED models.

* Moving slow tokenizer to the Trie world.

* Adding more docstrings to the Trie.

* Fixing doctest (incompatible wiht our format? )

* Update src/transformers/tokenization_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Adding a lot more comment into the internals of this algorithm.

* Cleaner doc.

* Fixing the namings.

* Update src/transformers/tokenization_utils.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* quality.

* Fixing longest first match.

* Small improvements to cuts + more test + canine resistant test.

* Fixing fast test.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

Fixes problems with passing int64 input to TF Seq2Seq models.

* Fix typo in deepspeed documentation

* Add missing import in deepspeed configuration

* Fix path in translation examples

* flax ner example

* added task to README

* updated readme

* 1. ArgumentParser -> HfArgumentParser
2. step-wise logging,eval and save

* added requirements.txt

* added progress bar

* updated README

* added check_min_version

* updated training data permuattion with JAX

* added metric lib to requirements

* updated readme table

* fixed imports

* Fix typo in deepspeed documentation

* Add missing import in deepspeed configuration

But does it really work?

* Implement object-detection pipeline

* Define threshold const

* Add `threshold` argument

* Refactor

* Uncomment test inputs

* `rm
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix typo
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix typo
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Chore better doc
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Rm unnecessary lines
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Chore better naming
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix typo

* Add `detr-tiny` for tests

* Add `ObjectDetectionPipeline` to `trnsfrmrs/init`

* Implement new bbox format

* Update detr post_process

* Update `load_img` method obj det pipeline

* make style

* Implement new testing format for obj det pipeln

* Add guard pytorch specific code in pipeline

* Add doc

* Make pipeline_obj_tet tests deterministic

* Revert some changes to `post_process` COCO api

* Chore

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Rm timm requirement

* make fixup

* Add timm requirement to test

* Make fixup

* Guard torch.Tensor

* Chore

* Delete unnecessary comment
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix Tensorflow T5 with int64 input

* Style pass

* Better error raised when cloned without lfs

* add from e

* Complete basic mechanism

* Save

* Complete everything

* Style & Quality

* Update READMEs

* Add testing

* Fix README.md format

* Apply suggestions

* Fix format

* Update utils/check_copies.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix logit_scale init

* add logit_scale_init_value as config param

* Deprecated Mirror

* revert

* revert

* revert

* fix

* [docs] update dead quickstart link on resuing past for GPT2

Thed dead link have been replaced by two links of forward and call methods of the GPT2 class for torch and tensorflow respectively.

* [docs] fix formatting for gpt2 page update

* Optimized bad word ids generation

* Fixed optimized bad token ids

* Updated style

* ✅ Update image-classification example's tests

* 🔥 remove cats_and_dogs test samples

* 💄 fix flake8

* Add conversion of TapasForMaskedLM

* Add copied from statements

* refactor GPT Config to allow dyn. properties

* make attribute_map a class attribute

* remove old code

* update unit test to test config: Add test for common properties setter

* update unit test to test config: Add test for common properties passed as parameters to __init__

* update to black code format

* Allow that setters are not defined for certain config classes

* update config classes to implement attribute_map

* bugfix lxmert config - id2labels was not defined when num_labels was set

* update broken configs - add attribute_maps

* update bart config

* update black codestyle

* update documentation on common config attributes

* update GPTJ config to new attribute map

* update docs on common attributes

* gptj config: add max_position_embeddings

* gptj config: format with black

* update speech to text 2 config

* format doc file to max_len 119

* update config template

* Adding a test for multibytes unicode.

* Adding some accents.

* Making sure decoding works.

* Make tests passing by being cheesy.

* Add inputs to pretrained tests

* Make style

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* ✨ add pytorch image classification example

* 🔥 remove utils.py

* 💄 fix flake8 style issues

* 🔥 remove unnecessary line

* ✨ limit dataset sizes

* 📌 update reqs

* 🎨 restructure - use datasets lib

* 🎨 import transforms directly

* 📝 add comments

* 💄 style

* 🔥 remove flag

* 📌 update requirement warning

* 📝 add vision README.md

* 📝 update README.md

* 📝 update README.md

* 🎨 add image-classification tag to model card

* 🚚 rename vision ➡️ image-classification

* 📝 update image-classification README.md

* [docs] Update perplexity.rst to use negative log likelihood

Model `forward` returns the negative log likelihood. The document correctly defines and calculates perplexity, but the description and variable names are inconsistent, which might cause confusion.

* [docs] restyle perplexity.rst