Instructions to use nirajp1/Sentiment_Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nirajp1/Sentiment_Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nirajp1/Sentiment_Analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nirajp1/Sentiment_Analysis") model = AutoModelForSequenceClassification.from_pretrained("nirajp1/Sentiment_Analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from nirajp1/Sentiment_Analysis: direct link, hf CLI and curl.
- Browser
- Download file 669 MB
-
https://huggingface.co/nirajp1/Sentiment_Analysis/resolve/main/model.safetensors
- Command line
-
hf download hf://nirajp1/Sentiment_Analysis/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/nirajp1/Sentiment_Analysis/resolve/main/model.safetensors
669 MB
- Xet hash:
- 02a6e607c63823c032e7c61e00324ed2d566bb68bcdd92698c0b96e6b3e33f0f
- Size of remote file:
- 669 MB
- SHA256:
- 0435c6c12c80a0a2206137c9fa8f6478fce4f4de88ac3d43d0f0e0da3c8c767b
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