* Initial callback proposal
* Finish various callbacks
* Post-rebase conflicts
* Fix tests
* Don't use something that's not set
* Documentation
* Remove unwanted print.
* Document all models can work
* Add tests + small fixes
* Update docs/source/internal/trainer_utils.rst
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Address review comments
* Fix TF tests
* Real fix this time
* This one should work
* Fix typo
* Really fix typo
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
- Use cuda:10.2 image instead of 10.1 (to address version mismatch
warning with pytorch)
- Use devel version that is built on the runtime and includes headers
and development tools (was otherwise failing to build apex)
* Create README.md
Model description for all LEGAL-BERT models, published as part of "LEGAL-BERT: The Muppets straight out of Law School". Chalkidis et al., 2018, In Findings of EMNLP 2020
* Update model_cards/nlpaueb/legal-bert-base-uncased/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
* Fixing top_k and min_length assertions, and a typo fix
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* PoC on RAG
* Format class name/obj name
* Better name in message
* PoC on one TF model
* Add PyTorch and TF dummy objects + script
* Treat scikit-learn
* Bad copy pastes
* Typo
'The class `AutoModelWithLMHead` is deprecated and will be removed in a future version. Please use `AutoModelForCausalLM` for causal language models, `AutoModelForMaskedLM` for masked language models and `AutoModelForSeq2SeqLM` for encoder-decoder models.'
I dont know how to change the 'How to use this model directly from the 🤗/transformers library:' part since it is not part of the model-paper
* 🚩 Add `power` argument for TF PolynomialDecay
* 🚩 Create default optimizer with power
* 🚩 Add argument to training args
* 🚨 Clean code format
* 🚨 Fix black warning
* 🚨 Fix code format
* configuration_squeezebert.py
thin wrapper around bert tokenizer
fix typos
wip sb model code
wip modeling_squeezebert.py. Next step is to get the multi-layer-output interface working
set up squeezebert to use BertModelOutput when returning results.
squeezebert documentation
formatting
allow head mask that is an array of [None, ..., None]
docs
docs cont'd
path to vocab
docs and pointers to cloud files (WIP)
line length and indentation
squeezebert model cards
formatting of model cards
untrack modeling_squeezebert_scratchpad.py
update aws paths to vocab and config files
get rid of stub of NSP code, and advise users to pretrain with mlm only
fix rebase issues
redo rebase of modeling_auto.py
fix issues with code formatting
more code format auto-fixes
move squeezebert before bert in tokenization_auto.py and modeling_auto.py because squeezebert inherits from bert
tests for squeezebert modeling and tokenization
fix typo
move squeezebert before bert in modeling_auto.py to fix inheritance problem
disable test_head_masking, since squeezebert doesn't yet implement head masking
fix issues exposed by the test_modeling_squeezebert.py
fix an issue exposed by test_tokenization_squeezebert.py
fix issue exposed by test_modeling_squeezebert.py
auto generated code style improvement
issue that we inherited from modeling_xxx.py: SqueezeBertForMaskedLM.forward() calls self.cls(), but there is no self.cls, and I think the goal was actually to call self.lm_head()
update copyright
resolve failing 'test_hidden_states_output' and remove unused encoder_hidden_states and encoder_attention_mask
docs
add integration test. rename squeezebert-mnli --> squeezebert/squeezebert-mnli
autogenerated formatting tweaks
integrate feedback from patrickvonplaten and sgugger to programming style and documentation strings
* tiny change to order of imports
* LayoutLM: add exception handling for bbox values
To replicate unhandled error:
- In `test_modelling_layoutlm.py` set `range_bbox=1025`, i.e. greater 1024
- Run `pytest tests/test_modeling_layoutlm.py`
Requirement for bbox values to be within the range 0-1000 is documented
but if it is violated then it isa not clear what is the issue from error
message.
* Update src/transformers/modeling_layoutlm.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Trainer should not modify its TrainingArguments
* Trainer should not modify its TrainingArguments
* Trainer should not modify its TrainingArguments
* Add test of resumed training
* Fixes
* Non multiGPU test
* Clean Trainer state
* Add more to the state
* Documentation
* One last test
* Make resume training test more complete
* Unwanted changes
Abhilash Majumder