Instructions to use DineshKumar1329/Sentiment_Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use DineshKumar1329/Sentiment_Analysis with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("DineshKumar1329/Sentiment_Analysis", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d33a3e8226199d5b87c5de060274fc5a6d33ef1133ce9be56cb58b059f7c6b4
- Size of remote file:
- 2.26 MB
- SHA256:
- d8087511b2217a8163f52f7b99a6148db8236f1e566d64855699879d6576b9a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.