Instructions to use bareeraqrsh/Sentiment-analysis-tool with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bareeraqrsh/Sentiment-analysis-tool with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bareeraqrsh/Sentiment-analysis-tool")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bareeraqrsh/Sentiment-analysis-tool") model = AutoModelForSequenceClassification.from_pretrained("bareeraqrsh/Sentiment-analysis-tool", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62186f69a920d47fecbe35da3b98920930192b5370dfd39ddb0624851b1e5cf4
- Size of remote file:
- 5.78 kB
- SHA256:
- 105e88235547957d72a7d668989c6c5feb323bc99986bac155da867245a38467
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