Instructions to use TakoData/en_tako_query_analyzer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- spaCy
How to use TakoData/en_tako_query_analyzer with spaCy:
!pip install https://huggingface.co/TakoData/en_tako_query_analyzer/resolve/main/en_tako_query_analyzer-any-py3-none-any.whl # Using spacy.load(). import spacy nlp = spacy.load("en_tako_query_analyzer") # Importing as module. import en_tako_query_analyzer nlp = en_tako_query_analyzer.load() - Notebooks
- Google Colab
- Kaggle
Download textcat_multilabel/model from TakoData/en_tako_query_analyzer: direct link, hf CLI and curl.
- Browser
- Download file 15.4 MB
-
https://huggingface.co/TakoData/en_tako_query_analyzer/resolve/main/textcat_multilabel/model
- Command line
-
hf download hf://TakoData/en_tako_query_analyzer/textcat_multilabel/model
-
curl -L -o model https://huggingface.co/TakoData/en_tako_query_analyzer/resolve/main/textcat_multilabel/model
15.4 MB
- Xet hash:
- a1d2e7047d4e8527b5bb214e5c7d1a18da47434cbbfebc7bae2125e2f3597de0
- Size of remote file:
- 15.4 MB
- SHA256:
- d9cf2c46c7490c9aa43b83356e1b2cec3e2db257ad4b36cd22c61ea92d9254fd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.