Instructions to use alokanand002/sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alokanand002/sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alokanand002/sentiment-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alokanand002/sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("alokanand002/sentiment-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6cddb4b3eddb56e9fb12c1dc111ba85ca2b6f7a1514c54cf0d1dcc0a8c57f388
- Size of remote file:
- 5.2 kB
- SHA256:
- 02d78d4ebbf0824607519e7234102d462a435c7d1f783bf0840a3a1e1a67cbac
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