Instructions to use binbin83/fr_on_value with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use binbin83/fr_on_value with spaCy:
!pip install https://huggingface.co/binbin83/fr_on_value/resolve/main/fr_on_value-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("fr_on_value") # Importing as module. import fr_on_value nlp = fr_on_value.load() - Notebooks
- Google Colab
- Kaggle
Download transformer/model from binbin83/fr_on_value: direct link, hf CLI and curl.
- Browser
- Download file 446 MB
-
https://huggingface.co/binbin83/fr_on_value/resolve/main/transformer/model
- Command line
-
hf download hf://binbin83/fr_on_value/transformer/model
-
curl -L -o model https://huggingface.co/binbin83/fr_on_value/resolve/main/transformer/model
446 MB
- Xet hash:
- 9fe92a6b817dc3f249f20105c44433029db5bce6bd3beb5527ec3e718a68fb87
- Size of remote file:
- 446 MB
- SHA256:
- cda9024fd0165a5c78c83ae6ad962311740d65b518cbde3bf571486417630b57
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