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:
- 430fcb6142305c96ce6f44317e8c3f0336b92bad56f033ff09c2ba6d5829cfc6
- Size of remote file:
- 2.24 GB
- SHA256:
- a015ba78bedeb37108fb77409b39df73dee293c567dad7b16be4a88fc5f77249
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