Instructions to use amjad-awad/skill-extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use amjad-awad/skill-extractor with spaCy:
!pip install https://huggingface.co/amjad-awad/skill-extractor/resolve/main/skill-extractor-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("skill-extractor") # Importing as module. import skill-extractor nlp = skill-extractor.load() - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 914b01d51978ec82a9f72c3ec3f29287c5cf88b004c55391cbaba09ea4df2221
- Size of remote file:
- 34.4 MB
- SHA256:
- 8346a08264ce43c53b4c16702c996a64b11d5dc2e70343b57c9b4fb7cb625a6a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.