Instructions to use Souvikcmsa/Roberta_Sentiment_Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Souvikcmsa/Roberta_Sentiment_Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Souvikcmsa/Roberta_Sentiment_Analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Souvikcmsa/Roberta_Sentiment_Analysis") model = AutoModelForSequenceClassification.from_pretrained("Souvikcmsa/Roberta_Sentiment_Analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Souvikcmsa/Roberta_Sentiment_Analysis: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/Souvikcmsa/Roberta_Sentiment_Analysis/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Souvikcmsa/Roberta_Sentiment_Analysis/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Souvikcmsa/Roberta_Sentiment_Analysis/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- 2dcd7b3b91a9986da74069c9b44246a1b785e8c44f6c40944f6c00e420525a42
- Size of remote file:
- 1.42 GB
- SHA256:
- e543c73d52e5dc02cfa2f5ab1e7710ff9cbf6d515c925807bc0514e02e9a8c3a
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