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Change-Id: I42cf780097456f5a8a9a9efc2a56e2c082d2a938 --- gnu/packages/machine-learning.scm | 55 +++++++++++++++++++++++++++++++ 1 file changed, 55 insertions(+) diff --git a/gnu/packages/machine-learning.scm b/gnu/packages/machine-learning.scm index 89fcd3c1b7..d1b282fea8 100644 --- a/gnu/packages/machine-learning.scm +++ b/gnu/packages/machine-learning.scm @@ -2480,6 +2480,61 @@ (define-public python-cutlery @end itemize") (license license:expat))) +(define-public python-curated-transformers + (package + (name "python-curated-transformers") + (version "0.1.0") + (source + (origin + (method url-fetch) + (uri (pypi-uri "curated-transformers" version)) + (sha256 + (base32 "04k54r5cxjl3l7xs4kx4cfnqsjr7gdlr577sp7sl7qgrk3kfqjbm")))) + (build-system pyproject-build-system) + (arguments + (list + #:test-flags + '(list ; Most ignored tests require network. + "--ignore=curated_transformers/tests/tokenizers/test_auto_tokenizer.py" + "-k" (string-append "not test_special_pieces" + " and not test_auto_encoder" + " and not test_auto_decoder" + " and not test_auto_causal_lm" + " and not test_from_hf_hub_to_cache" + " and not test_from_hf_hub_to_cache_legacy" + " and not test_checkpoint_type_without_safetensors" + " and not test_hf_hub_failures" + ;; These have been added when downgrading curated_tokenizers. + " and not test_camembert_tokenizer_toy_tokenizer" + " and not test_roberta_tokenizer" + " and not test_xlmr_toy_tokenizer")))) + (propagated-inputs (list python-catalogue + python-cutlery + python-huggingface-hub + python-pytorch + python-tokenizers)) + (native-inputs (list python-pytest)) + (home-page "https://github.com/explosion/curated-transformers") + (synopsis "PyTorch library of transformer models and components") + (description + "This package provides a @code{PyTorch} library of transformer models and +components. It helps to download state-of-the-art models that are composed +from a set of reusable components. The stand-out features of Curated +Transformer are: + +@itemize +@item Supports state-of-the art transformer models, including LLMs such as +Falcon, Llama, and Dolly v2. +@item Each model is composed from a set of reusable building blocks, providing +many benefits: implementing a feature or bugfix benefits all models ; Adding +new models to the library is low-effort. +@item Consistent type annotations of all public APIs, hence a great coding +support from IDEs. Integrates well with your existing type-checked code. +@item Great for education, because the building blocks are easy to study. +@item Minimal dependencies. +@end itemize") + (license license:expat))) + (define-public python-autograd (let* ((commit "c6d81ce7eede6db801d4e9a92b27ec5d409d0eab") (revision "0")