Instructions to use ScriptEdgeAI/MarathiSentiment-Bloom-560m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ScriptEdgeAI/MarathiSentiment-Bloom-560m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ScriptEdgeAI/MarathiSentiment-Bloom-560m")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ScriptEdgeAI/MarathiSentiment-Bloom-560m") model = AutoModelForSequenceClassification.from_pretrained("ScriptEdgeAI/MarathiSentiment-Bloom-560m") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1cb5906e52ccfcc712639d66d92ce6b3458d11b3416c1ccde9046d1ad5c1ab3a
- Size of remote file:
- 14.5 MB
- SHA256:
- 8a6b9dd8239a509474806a8918e5fc77e760d9362fe12351532b2a8e969c082b
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