Instructions to use ninja/Sentiment_Analysis2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ninja/Sentiment_Analysis2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ninja/Sentiment_Analysis2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ninja/Sentiment_Analysis2") model = AutoModelForSequenceClassification.from_pretrained("ninja/Sentiment_Analysis2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8965bdb47b28df05b7eeddfd9397846e049128f101bfc10225ca1903283a3027
- Size of remote file:
- 434 MB
- SHA256:
- cca8fc2d2e89106279af9d7f3cd9bc78cdf301180676dad8b06842447142f302
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