Instructions to use filbench/tl_hash_transition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use filbench/tl_hash_transition with spaCy:
!pip install https://huggingface.co/filbench/tl_hash_transition/resolve/main/tl_hash_transition-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("tl_hash_transition") # Importing as module. import tl_hash_transition nlp = tl_hash_transition.load() - Notebooks
- Google Colab
- Kaggle
Download tok2vec/model from filbench/tl_hash_transition: direct link, hf CLI and curl.
- Browser
- Download file 34.3 MB
-
https://huggingface.co/filbench/tl_hash_transition/resolve/main/tok2vec/model
- Command line
-
hf download hf://filbench/tl_hash_transition/tok2vec/model
-
curl -L -o model https://huggingface.co/filbench/tl_hash_transition/resolve/main/tok2vec/model
34.3 MB
- Xet hash:
- e4429daeb4fd8f2eca6f1b99da9664a93d321d96a2f6384c18a56c71b7435bb3
- Size of remote file:
- 34.3 MB
- SHA256:
- 7e72441e0b49a98821c515a19f79c317f4a48562ce7e5b0b4168e285c63a0570
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