Instructions to use spacy/en_core_web_sm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use spacy/en_core_web_sm with spaCy:
!pip install https://huggingface.co/spacy/en_core_web_sm/resolve/main/en_core_web_sm-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_core_web_sm") # Importing as module. import en_core_web_sm nlp = en_core_web_sm.load() - Notebooks
- Google Colab
- Kaggle
Download tok2vec/model from spacy/en_core_web_sm: direct link, hf CLI and curl.
- Browser
- Download file 6.27 MB
-
https://huggingface.co/spacy/en_core_web_sm/resolve/main/tok2vec/model
- Command line
-
hf download hf://spacy/en_core_web_sm/tok2vec/model
-
curl -L -o model https://huggingface.co/spacy/en_core_web_sm/resolve/main/tok2vec/model
6.27 MB
- Xet hash:
- 60b71aa43bd80f35fc732f47b03e2f3ef4d29035f43171fd5d1951d4d44e9edf
- Size of remote file:
- 6.27 MB
- SHA256:
- 42d8414521eaf75f817bd1b351b26039a22a912bb2617f95ead305420f2ebffd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.