GitLab

* zero chance anyone's using that constant no?

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

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

* `make style`

Currently, tensorflow examples use the `load_metric` function from
Datasets library, commit migrates function call to `load` function
from Evaluate library.

* [Flax] Fix incomplete batches in example scripts

* fix dataloader batching

* convert jnp batch idxs to np array

* add missing `pad_shard_unpad` to final prediction generate step

* only `pad_shard_unpad` at inference time

* merge conflicts

* remove incomplete batch step from eval

* fix run_qa.py

* add `pad_shard_unpad` to run_flax_ner.py

* add `pad_shard_unpad` to run_flax_glue.py

* add `pad_shard_unpad` to run_image_classification.py

* make style

* fix mlm flax eval batches

* remove redundant imports

* generalize decay_mask_fn to find all layernorm params

* fixup

* generalising decay_mask_fn

* 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

1. Fixes evaluation errors popping up when you train/eval on squad v2 (one was newly encountered and one that was previously reported Running SQuAD 1.0 sample command raises IndexError #15401 but not completely fixed).
2. Removes boolean arguments that don't use store_true. Please, don't use these: *ANY non-empty string is being converted to True in this case and this clearly is not the desired behavior (and it creates a LOT of confusion).
3. All no-trainer test scripts are now saving metric values in the same way (with the right prefix eval_), which is consistent with the trainer-based versions.
4. Adds forgotten model.eval() in the no-trainer versions. This improved some results, but not everything (see the discussion in the end). Please, see the F1 scores and the discussion below.

* 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

* Split file_utils in several submodules

* Fixes

* Add back more objects

* More fixes

* Who exactly decided to import that from there?

* Second suggestion to code with code review

* Revert wront move

* Fix imports

* Adapt all imports

* Adapt all imports everywhere

* Revert this import, will fix in a separate commit

* Updates the default branch from master to main

* Links from `master` to `main`

* Typo

* Update examples/flax/README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Harder check for IndexErrors in QA scripts

* Make test stronger

* use custom training arguments

* update tests

* make tensorboard optional

* update test_fetcher for flax examples

* make the tests slow

* add test for glue

* add tests for clm

* fix clm test

* add summrization tests

* more tests

* fix few tests

* add test for t5 mlm

* fix t5 mlm test

* fix tests for multi device

* cleanup

* ci job

* fix metric file name

* make t5 more robust

* #12789 Replace assert statements with exceptions

* fix-copies: made copy changes to utils_qa.py in examples/pytorch/question-answering and examples/tensorflow/question-answering

* minor refactor for clarity

* use Repository for push_to_hub

* update readme

* update other flax scripts

* update readme

* update qa example

* fix push_to_hub call

* fix typo

* fix more typos

* update readme

* use abosolute path to get repo name

* fix glue script

* flax qa example

* Updated README:  Added Large model

* added utils_qa.py FULL_COPIES

* Updates:
1. Copyright Year updated
2. added dtype arg
3. passing seed and dtype to load model
4. Check eval flag before running eval

* updated README

* updated code comment