* add examples subfolder
* mention examples in codeparrot readme
* use Trainer optimizer and scheduler type and add output_dir as argument
* add example of text-to-python and python-to-text models
* mention the downstream examples in the readme
* fix typo
* examples: add Bloom support for token classification (FLAX, PyTorch and TensorFlow)
* examples: remove support for Bloom in token classication (FLAX and TensorFlow currently have no support for it)
* Update run_translation_no_trainer.py
found an error in selecting `no_decay` parameters and some small modifications when the user continues to train from a checkpoint
* fixs `no_decay` and `resume_step` issue
1. change `no_decay` list
2. if use continue to train their model from provided checkpoint, the `resume_step` will not be initialized properly if `args.gradient_accumulation_steps != 1`
* 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>
* Added accelerate gradient accumulation wrapper to run_image_classification_no_trainer.py example script
* make fixup changes
* PR comments
* changed input to Acceletor based on PR comment, ran make fixup
* Added comment explaining the sync_gradients statement
* Fixed lr scheduler max steps
* Changed run_clm_no_trainer.py script to use accelerate gradient accum wrapper
* Fixed all scripts except wav2vec2 pretraining to use accelerate gradient accum wrapper
* Added accelerate gradient accum wrapper for wav2vec2_pretraining_no_trainer.py script
* make fixup and lr_scheduler step inserted back into run_qa_beam_search_no_trainer.py
* removed changes to run_wav2vec2_pretraining_no_trainer.py script and fixed using wrong constant in qa_beam_search_no_trainer.py script
* Delete valohai.yaml
* NLP => ML
* typo
* website supports https
* datasets
* 60k + modalities
* unrelated link fixing for accelerate
* Ok those links were actually broken
* Fix link
* Make `AutoTokenizer` auto-link
* wording tweak
* add at least one non-nlp task
Comparisons like
version.parse(torch.__version__) > version.parse("1.6")
are True for torch==1.6.0+cu101 or torch==1.6.0+cpu
version.parse(version.parse(torch.__version__).base_version) are preferred (and available in pytorch_utils.py
Currently, tensorflow examples use the `load_metric` function from
Datasets library, commit migrates function call to `load` function
from Evaluate library.
* Migrate metric to Evaluate library in tf examples
Currently tensorflow examples use `load_metric` function from Datasets
library , commit migrates function call to `load` function to
Evaluate library.
Fix for #18306
* Migrate metric to Evaluate library in tf examples
Currently tensorflow examples use `load_metric` function from Datasets
library , commit migrates function call to `load` function to
Evaluate library.
Fix for #18306
* Migrate `metric` to Evaluate for all tf examples
Currently tensorflow examples use `load_metric` function from Datasets
library , commit migrates function call to `load` function to
Evaluate library.
* add info about megatron training
* upload models and datasets from CodeParrot organization
* upload models and datasets from CodeParrot organization
* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* fix typo and add comment about codeparrot vs megatron
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* Fix RESOURCE_EXHAUSTED error for large datasets on Flax example scripts
* using np.permutation for creating batch_idx
* train_samples_idx -> training_samples_idx
* fix type hints
