GitLab

* Pin Keras for now out of paranoia

* Add the keras pin to _tests_requirements.txt too

* Make sure the Keras version matches the TF one

* make fixup

Add missing spaces in adjacent strings

* refactor: change default block_size

* fix: return tf to origin

* fix: change files to origin

* rebase

* rebase

* rebase

* rebase

* rebase

* rebase

* rebase

* rebase

* refactor: add min block_size to files

* reformat: add min block_size for run_clm tf

Fixed a few typos

* docs: add space to docs

* docs: remove reduntant space

* Revert frozen training arguments

* TODO

* Update the TF pin and see if anything breaks

* make fixup

* make fixup

* make fixup

* Make training args fully immutable

* Working tests, PyTorch

* In test_trainer

* during testing

* Use proper dataclass way

* Fix test

* Another one

* Fix tf

* Lingering slow

* Exception

* Clean

* add missing tokens

* fix

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

* pytorch examples

* pytorch mim no trainer

* cookiecutter

* flax examples

* missed line in pytorch run_glue

* tensorflow examples

* tensorflow run_clip

* tensorflow run_mlm

* tensorflow run_ner

* tensorflow run_clm

* pytorch example from_configs

* pytorch no trainer examples

* Revert "tensorflow run_clip"

This reverts commit 261f86ac1f1c9e05dd3fd0291e1a1f8e573781d5.

* fix: duplicated argument

* fix

* fix

* fix

* fix

* fix

* fix

* fix

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

* pytorch examples

* tensorflow examples

* flax examples

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

* fix loading dataset link

* Update examples/tensorflow/translation/run_translation.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Update examples/tensorflow/translation/run_translation.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

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Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* An end to accursed version-specific imports

* No more K.is_keras_tensor() either

* Update dependency tables

* Use a cleaner call context function getter

* Add a cap to <2.14

* Add cap to examples requirements too

* Add an option to reduce compile() console spam

* Add annotations to the example scripts

* Add notes to the quicktour docs as well

* minor fix

* Fix no such file or directory error

* Address comment

* Fix formatting issue

* Proposed fix for TF example now running on safetensors.

* Adding more warnings and returning keys.

* Trigger CI

* Trigger CI

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Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

minor refactoring to allow compatible datasets to work.

Remove accelerate from tf

* add: tokenizer training script for TF TPU LM training.

* add: script for preparing the TFRecord shards.

* add: sequence of execution to readme.

* remove limit from the tfrecord shard name.

* Add initial train_model.py

* Add basic training arguments and model init

* Get up to the point of writing the data collator

* Pushing progress so far!

* Complete first draft of model training code

* feat: grouping of texts efficiently.
Co-authored-by: Matt <rocketknight1@gmail.com>

* Add proper masking collator and get training loop working

* fix: things.

* Read sample counts from filenames

* Read sample counts from filenames

* Draft README

* Improve TPU warning

* Use distribute instead of distribute.experimental

* Apply suggestions from code review
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Modularize loading and add MLM probability as arg

* minor refactoring to better use the cli args.

* readme fillup.

* include tpu and inference sections in the readme.

* table of contents.

* parallelize maps.

* polish readme.

* change script name to run_mlm.py

* address PR feedback (round I).

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Co-authored-by: Matt <rocketknight1@gmail.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Pin tensorflow-text to go with tensorflow

* Make it more convenient to pin TensorFlow

* setup don't like f-strings

* Stop requiring Torch for our TF examples!

* Slight tweak to logging in the example itself

* Initial commit

* stash commit

* Add model checkpointing and pushing

* Fix model name inference

* Update README

* Update README

* Remove a couple of Torch references

* Update copyright date

* make fixup

* Update PushToHubCallback args!

* Remove the torch summary

* Add strategy.scope

* Add check for different embedding types in examples

* Correctly update summarization example

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

* TF image classification script

* Update requirements

* Fix up

* Add tests

* Update test fetcher
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix directory path

* Adding `zero-shot-object-detection` pipeline doctest. (#20274)

* Adding `zero-shot-object-detection` pipeline doctest.

* Remove nested_simplify.

* Add generate kwargs to `AutomaticSpeechRecognitionPipeline` (#20952)

* Add generate kwargs to AutomaticSpeechRecognitionPipeline

* Add test for generation kwargs

* Trigger CI

* Data collator returns np

* Update feature extractor -> image processor

* Bug fixes - updates to reflect changes in API

* Update flags to match PT & run faster

* Update instructions - Maria's comment

* Update examples/tensorflow/image-classification/README.md

* Remove slow decorator

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Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: bofeng huang <bofenghuang7@gmail.com>
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

Return NP instead of TF tensors for our data loading pipeline