Instructions to use magepol/en_generic_big with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use magepol/en_generic_big with spaCy:
!pip install https://huggingface.co/magepol/en_generic_big/resolve/main/en_generic_big-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_generic_big") # Importing as module. import en_generic_big nlp = en_generic_big.load() - Notebooks
- Google Colab
- Kaggle
Download textcat/model from magepol/en_generic_big: direct link, hf CLI and curl.
- Browser
- Download file 3.94 MB
-
https://huggingface.co/magepol/en_generic_big/resolve/main/textcat/model
- Command line
-
hf download hf://magepol/en_generic_big/textcat/model
-
curl -L -o model https://huggingface.co/magepol/en_generic_big/resolve/main/textcat/model
3.94 MB
- Xet hash:
- bf1137838f2df3fc2cfc339cd63b4e8ec2779dade242b63cf3dbffbcb8855647
- Size of remote file:
- 3.94 MB
- SHA256:
- 23f3fc6dfa6ee8c1a4bce9704c9dfabeaf6ccf1a5ed5d292cdf36cc715511f73
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.