Instructions to use aashish-249/Sentiment_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aashish-249/Sentiment_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="aashish-249/Sentiment_classification")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("aashish-249/Sentiment_classification") model = AutoModel.from_pretrained("aashish-249/Sentiment_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c02f3980769c4c321e3a0abe0699c5583c991cc075faf8553ddab8e6d21c7f1
- Size of remote file:
- 711 MB
- SHA256:
- f64bf1f24744bb47e887aa1aa99d998fe0bd88d6a7ce55b92bae13b00f95b058
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