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
* Add logits_processor parameter, used by `generate`, to `Seq2SeqTrainer` methods `evaluate` and `predict`
* Add all generate parameters to `Seq2SeqTrainer`, and also to `QuestionAnsweringSeq2SeqTrainer` which overrides it
* Remove `self._num_beams` from trainer classes
* - Run fixup
- Fix "Constraint" not exposed
- Fix synced_gpus to actually read from param
* Use kwargs
* Copy kwargs before making changes to it
* Fix style issues unused imports
* deduplication draft
* update style
* update style test
* dummy test main
* rename modules
* rename functions
* return extremes in deduplicate_clusters
* update style
* cast str for gzip
* update doc string
* time processing
* use dataset map to compute minhash
* fill value for short token
* remove da map method
* update style
* use share object to multiprocess
* update style
* use f-string and minor fix
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>
* update style
* use module parameters
* change ds_dedup to ds_filter
* save ds_dedup
* mv test to script tests
* make jaccard threshold a parameter of deduplicate_dataset
* update style
* add doc strings
* update style
* add doc string for DuplicationIndex
* save files into data dir
* update readme
* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>
* make near deduplication optional
* move near deduplication in README
* Update examples/research_projects/codeparrot/README.md
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* use f string
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
Co-authored-by: Loubna Ben Allal <44069155+loubnabnl@users.noreply.github.com>
* Raise RepoNotFoundError in case of 401
* Include changes from revert-17646-skip_repo_not_found
* Add a comment
* 💄 Code quality
* 💚 Update `get_from_cache` test
* 💚 Code quality & skip failing test
* Add examples telemetry
* Alternative approach
* Add to all other examples
* Add to templates as well
* Put framework separately
* Same for TensorFlow
* Make forward pass work
* More improvements
* Remove unused imports
* Remove timm dependency
* Improve loss calculation of token classifier
* Fix most tests
* Add docs
* Add model integration test
* Make all tests pass
* Add LayoutLMv3FeatureExtractor
* Improve integration test + make fixup
* Add example script
* Fix style
* Add LayoutLMv3Processor
* Fix style
* Add option to add visual labels
* Make more tokenizer tests pass
* Fix more tests
* Make more tests pass
* Fix bug and improve docs
* Fix import of processors
* Improve docstrings
* Fix toctree and improve docs
* Fix auto tokenizer
* Move tests to model folder
* Move tests to model folder
* change default behavior add_prefix_space
* add prefix space for fast
* add_prefix_spcae set to True for Fast
* no space before `unique_no_split` token
* add test to hightligh special treatment of added tokens
* fix `test_batch_encode_dynamic_overflowing` by building a long enough example
* fix `test_full_tokenizer` with add_prefix_token
* Fix tokenizer integration test
* Make the code more readable
* Add tests for LayoutLMv3Processor
* Fix style
* Add model to README and update init
* Apply suggestions from code review
* Replace asserts by value errors
* Add suggestion by @ducviet00
* Add model to doc tests
* Simplify script
* Improve README
* a step ahead to fix
* Update pair_input_test
* Make all tokenizer tests pass - phew
* Make style
* Add LayoutLMv3 to CI job
* Fix auto mapping
* Fix CI job name
* Make all processor tests pass
* Make tests of LayoutLMv2 and LayoutXLM consistent
* Add copied from statements to fast tokenizer
* Add copied from statements to slow tokenizer
* Remove add_visual_labels attribute
* Fix tests
* Add link to notebooks
* Improve docs of LayoutLMv3Processor
* Fix reference to section
Co-authored-by: SaulLu <lucilesaul.com@gmail.com>
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* average loss over batches and accumulated steps for tracking
* fix layernorm weight decay
* use AdamW from Pytorch instead of Transformers
* add shuffling of sequences inside the batches
* add shuffling of sequences inside the batches
* add logging dir and reformat code
* fix lr tracking
* remove Mistral scaling
* keep Mistral scaling
* reformat code
* fix error
* fix error
* use shuffling function from Pytorch
* remove argument for shuffling batch sequences as it isn't optional
* update package versions and install accelerate from source
* remove unused package
* Update loss average over accumulated steps
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* Update loss average over accumulated steps
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* use one shuffle buffer argument
* compute avg_loss in one line
Co-authored-by: Loubna ben allal <loubnabenallal@gmail.com>
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
