* HerBERT transformer model for Polish language understanding.
* HerbertTokenizerFast generated with HerbertConverter
* Herbert base and large model cards
* Herbert model cards with tags
* Herbert tensorflow models
* Herbert model tests based on Bert test suit
* src/transformers/tokenization_herbert.py edited online with Bitbucket
* src/transformers/tokenization_herbert.py edited online with Bitbucket
* docs/source/model_doc/herbert.rst edited online with Bitbucket
* Herbert tokenizer tests and bug fixes
* src/transformers/configuration_herbert.py edited online with Bitbucket
* Copyrights and tests for TFHerbertModel
* model_cards/allegro/herbert-base-cased/README.md edited online with Bitbucket
* model_cards/allegro/herbert-large-cased/README.md edited online with Bitbucket
* Bug fixes after testing
* Reformat modified_only_fixup
* Proper order of configuration
* Herbert proper documentation formatting
* Formatting with make modified_only_fixup
* Dummies fixed
* Adding missing models to documentation
* Removing HerBERT model as it is a simple extension of BERT
* Update model_cards/allegro/herbert-base-cased/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
* Update model_cards/allegro/herbert-large-cased/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
* HerbertTokenizer deprecated configuration removed
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
in `tests/test_utils_check_copies.py` I was getting intermittently:
```
utils/check_copies.py:52
/mnt/nvme1/code/transformers-comet/utils/check_copies.py:52: DeprecationWarning: invalid escape sequence \s
while line_index < len(lines) and re.search(f"^{indent}(class|def)\s+{name}", lines[line_index]) is None:
```
So this should fix it.
* model card for bert-base-NER
* add meta data up top
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
- TFAutoModelForCausalLM
- TFAutoModelForMaskedLM
- TFAutoModelForSeq2SeqLM
as per deprecation warning. No tests as it simply removes current
warnings from tests.
* Improving Pipelines by defaulting to framework='tf' when
pytorch seems unavailable.
* Actually changing the default resolution order to account for model
defaults
Adding a new tests for each pipeline to check that pipeline(task) works
too without manually adding the framework too.
* use DDP no_sync when possible
* fix is_nlp_available addition mistake
* reformat trainer.py
* reformat trainer.py
* drop support for pytorch < 1.2
* return support for pytorch < 1.2
* Do not softmax when num_labels==1
* Update src/transformers/pipelines.py
Co-authored-by: Funtowicz Morgan <mfuntowicz@users.noreply.github.com>
Co-authored-by: Funtowicz Morgan <mfuntowicz@users.noreply.github.com>
* Add Documentation for GPT-1 Classification
* Add GPT-1 with Classification head
* Add tests for GPT-1 Classification
* Add GPT-1 For Classification to auto models
* Remove authorized missing keys, change checkpoint to openai-gpt
