0.1.6

0.1.6 / 2023-11-15

• rationalize dependencies
• update to include the KenLMModel example in README

0.1.4 / 2023-11-14

• version bump; release
• Merge branch 'benlipkin/main' into main
• add simple surprisal compute test that should pass as long as full surprise() method executes. no assertions are made.
• implement attention mask for use_bos_token token case
• Merge branch 'main' of github.com:benlipkin/surprisal into benlipkin/main
• Merge branch 'main' of github.com:aalok-sathe/surprisal into main
• Merge pull request #14 from aalok-sathe/feature-support-kenlm
• OK, we have a MWE! still TODO: figure out surprisal value: do we want that? maybe add an option to show but default to disabling it? do we also want bos?
• bugfix in ids handling in CustomEncoding
• bugfixes; bump numpy version for typing
• make KenLMModel visible at the module level
• add an KenLM and NGramSurprisal implementation
• move repr() to SurprisalArray rather than huggingfacesurprisal. complete CustomEncoding implementation.
• actually no point subclassing from tokenizers.Encoding
• flesh out interface towards supporting CustomEncoding for custom-tokenized text, e.g. whitespace for kenlm
• Update python-publish.yml: fix poetry install command
• Update pylint.yml: fix poetry install command
• add deps to publish action workspace using poetry
• Update pylint.yml
• Create python-publish.yml
• Create pylint.yml
• start writing kenLM implementation
• prefix with hf to indicate it works with HF-based tokenizer outputs
• explicitly specify attention mask
• fix concat on device
• always pad right
• add arg to trust remote code
• require torch2+ to take advantage of optimizations
• added support for fp16 and bf16 precision

surprisal 0.1.4

Live on PyPI.org: https://pypi.org/project/surprisal/