v1.1.0rc1
Pre-releaseFirst v1.1 pre-release candidate. See the corresponding allennlp v1.1.0rc1 release candidate.
What's new since v1.0.0
Fixed
- Updated the BERT SRL model to be compatible with the new huggingface tokenizers.
CopyNetSeq2Seq
model now works with pretrained transformers.- A bug with
NextTokenLM
that caused simple gradient interpreters to fail. - A bug in
training_config
ofqanet
andbimpm
that used the old version ofregularizer
andinitializer
. - The fine-grained NER transformer model did not survive an upgrade of the transformers library, but it is now fixed.
- Fixed many minor formatting issues in docstrings. Docs are now published at https://docs.allennlp.org/models/.
Changed
CopyNetDatasetReader
no longer automatically addsSTART_TOKEN
andEND_TOKEN
to the tokenized source. If you want these in the tokenized source, it's up to
the source tokenizer.
Added
- Added two models for fine-grained NER
- Added a category for multiple choice models, including a few reference implementations
- Implemented manual distributed sharding for SNLI dataset reader.
Commits
dd60f94 Prepare for release v1.1.0rc1
da83a4e build and publish models docs (#91)
4b2178b implement manual distributed sharding for SNLI reader (#89)
1a2a8f4 Updates the SRL model (#93)
8a93743 Updated the fine-grained NER transformer model (#92)
b913333 Multiple Choice (#75)
09395d2 updates for new transformers release (#88)
11c6814 fix the bug of bimpm and update CHANGELOG (#87)
a735ddd Fix the regularizer of QANet model (#86)
0ce14da fixes for next_token_lm (#85)
37136f8 skip docker build on nightly release
82aa9ac Fine grained NER (#84)
4b5b939 fix test fixture
947beb0 remove unused param in copynet reader
9ec65df fix nightly Docker workflow
3019a4e fix workflow skip conditions
cc60ab9 use small dummy transformer for copynet test (#83)
ac9f214 fix nightly workflow
596e6a7 Bump mypy from 0.781 to 0.782 (#82)
d210c2f add nightly releases (#81)
935a2a8 dont add START and END tokens to source in CopyNet (#79)
d6798ce update skip conditions on const-parser-test (#80)
2754f88 Bump mypy from 0.780 to 0.781 (#78)
d3588ad Make CopyNet work with pretrained transformer models (#76)