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 sample_input.pkl from Souvikcmsa/Roberta_Sentiment_Analysis: direct link, hf CLI and curl.
- Browser
- Download file 2.03 kB
-
https://huggingface.co/Souvikcmsa/Roberta_Sentiment_Analysis/resolve/main/sample_input.pkl
- Command line
-
hf download hf://Souvikcmsa/Roberta_Sentiment_Analysis/sample_input.pkl
-
curl -L -o sample_input.pkl https://huggingface.co/Souvikcmsa/Roberta_Sentiment_Analysis/resolve/main/sample_input.pkl
2.03 kB
- Xet hash:
- d6d019fb1d4570c39c527d4d945283a65fe9ff4e0279b53a53598cfd8e9abfaa
- Size of remote file:
- 2.03 kB
- SHA256:
- 077ccb8d3a09b2935ff298b56394bdf352a4aa01fa67673c8b35c1da4d47380e
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