GitLab

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

* docs: add space to docs

* docs: remove reduntant space

* Revert frozen training arguments

* TODO

* 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>

* Add an option to reduce compile() console spam

* Add annotations to the example scripts

* Add notes to the quicktour docs as well

* minor fix

* 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

Return NP instead of TF tensors for our data loading pipeline

* Only resize embeddings when necessary

* Add comment

* Finished QA example

* Dodge a merge conflict

* Update text classification and LM examples

* Update NER example

* New Keras metrics WIP, fix NER example

* Update NER example

* Update MC, summarization and translation examples

* Add XLA warnings when shapes are variable

* Make sure batch_size is consistently scaled by num_replicas

* Add PushToHubCallback to all models

* Add docs links for KerasMetricCallback

* Add docs links for prepare_tf_dataset and jit_compile

* Correct inferred model names

* Don't assume the dataset has 'lang'

* Don't assume the dataset has 'lang'

* Write metrics in text classification

* Add 'framework' to TrainingArguments and TFTrainingArguments

* Export metrics in all examples and add tests

* Fix training args for Flax

* Update command line args for translation test

* make fixup

* Fix accidentally running other tests in fp16

* Remove do_train/do_eval from run_clm.py

* Remove do_train/do_eval from run_mlm.py

* Add tensorflow tests to circleci

* Fix circleci

* Update examples/tensorflow/language-modeling/run_mlm.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update examples/tensorflow/test_tensorflow_examples.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update examples/tensorflow/translation/run_translation.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update examples/tensorflow/token-classification/run_ner.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Fix save path for tests

* Fix some model card kwargs

* Explain the magical -1000

* Actually enable tests this time

* Skip text classification PR until we fix shape inference

* make fixup
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* zero chance anyone's using that constant no?

* `transformers-cli login` => `huggingface-cli login`

* `transformers-cli repo create` => `huggingface-cli repo create`

* `make style`

* Add examples telemetry

* Alternative approach

* Add to all other examples

* Add to templates as well

* Put framework separately

* Same for TensorFlow

* Black preview

* Fixup too!

* Fix check copies

* Use the same version as the CI

* Bump black

* fix formatting and remove use_auth

* Add use_auth_token to Flax examples

* [examples] max samples can't be bigger than then len of dataset

* do tf and flax

* use block_size instead of max_seq_length

* fixup

* remove pad_to_block_size
Co-authored-by: Russell Klopfer <russell@kloper.us>

* Replace outdated model tags with their now-canonical pipeline types

* spam the CI till it's green

* remove sum for list flattening

* change to chain(*)

* make chain object a list

* delete empty lines

per sgugger's suggestions
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Nicholas Broad <nicholas@nmbroad.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fixing requirements for TF LM models and use correct model mappings

* make style

* examples: only use keep_linebreaks when reading TXT files for all CLM examples

* examples: only use keep_linebreaks when reading TXT files for all CLM examples

* examples: only use keep_linebreaks when reading TXT files for all CLM examples

* examples: add keep_linebreaks option to text dataset loader for all CLM examples

* examples: introduce new keep_linebreaks option as data argument in CLM examples

* Fixed train_test_split test_size argument

* `Seq2SeqTrainer` set max_length and num_beams only when non None  (#12899)

* set max_length and num_beams only when non None

* fix instance variables

* fix code style

* [FLAX] Minor fixes in CLM example (#12914)

* readme: fix retrieval of vocab size for flax clm example

* examples: fix flax clm example when using training/evaluation files

* Fix module path for symbolic_trace example
Co-authored-by: cchen-dialpad <47165889+cchen-dialpad@users.noreply.github.com>
Co-authored-by: Stefan Schweter <stefan@schweter.it>
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>

* Validation split added: custom data files

Validation split added in case of no validation file and loading custom data

* Updated documentation with custom file usage

Updated documentation with custom file usage

* Update README.md

* Update README.md

* Update README.md

* Made some suggested stylistic changes

* Used logger instead of print.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Made similar changes to add validation split

In case of a missing validation file, a validation split will be used now.

* max_train_samples to be used for training only

max_train_samples got misplaced, now corrected so that it is applied on training data only, not whole data.

* styled

* changed ordering

* Improved language of documentation
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Improved language of documentation
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fixed styling issue

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

* Tensorflow MLM example

* Add CLM example

* Style fixes, adding missing checkpoint code from the CLM example

* Fix TPU training, avoid massive dataset warnings

* Fix incorrect training length calculation for multi-GPU training

* Fix incorrect training length calculation for multi-GPU training

* Refactors and nitpicks from the review

* Style pass

* Adding README