* Fix typos and grammar mistakes in docs and examples
* Fix typos in docstrings and comments
* Fix spelling of `tokenizer` in model tests
* Remove erroneous spaces in decorators
* Remove extra spaces in Markdown link texts
* Port core files + ESM (because ESM code is odd)
* Search-replace in modelling code
* Fix up transfo_xl as well
* Fix other core files + tests (still need to add correct import to tests)
* Fix cookiecutter
* make fixup, fix imports in some more core files
* Auto-add imports to tests
* Cleanup, add imports to sagemaker tests
* Use correct exception for importing tf_keras
* Fixes in modeling_tf_utils
* make fixup
* Correct version parsing code
* Ensure the pipeline tests correctly revert to float32 after each test
* Ensure the pipeline tests correctly revert to float32 after each test
* More tf.keras -> keras
* Add dtype cast
* Better imports of tf_keras
* Add a cast for tf.assign, just in case
* Fix callback imports
While using `run_clm.py`,[^1] I noticed that some files were being added
to my global cache, not the local cache. I set the `cache_dir` parameter
for the one call to `evaluate.load()`, which partially solved the
problem. I figured that while I was fixing the one script upstream, I
might as well fix the problem in all other example scripts that I could.
There are still some files being added to my global cache, but this
appears to be a bug in `evaluate` itself. This commit at least moves
some of the files into the local cache, which is better than before.
To create this PR, I made the following regex-based transformation:
`evaluate\.load\((.*?)\)` -> `evaluate\.load\($1,
cache_dir=model_args.cache_dir\)`. After using that, I manually fixed
all modified files with `ruff` serving as useful guidance. During the
process, I removed one existing usage of the `cache_dir` parameter in a
script that did not have a corresponding `--cache-dir` argument
declared.
[^1]: I specifically used `pytorch/language-modeling/run_clm.py` from
v4.34.1 of the library. For the original code, see the following URL:
acc394c4f5/examples/pytorch/language-modeling/run_clm.py.
* Remove the torch main_process_first context manager from TF examples
* Correctly set num_beams=1 in our examples, and add a guard in GenerationConfig.validate()
* Update src/transformers/generation/configuration_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* 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
* 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
* 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
* Proposed fix for TF example now running on safetensors.
* Adding more warnings and returning keys.
* Trigger CI
* Trigger CI
---------
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
* 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).
---------
Co-authored-by: Matt <rocketknight1@gmail.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
