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:
- 5cc7590918f974b32d02a5e4fd0901c465a91be4ff025daf5be1e6014dc510cb
- Size of remote file:
- 2.24 GB
- SHA256:
- 4e511339f23b2c10c6c2c7c247f9eeda7639872acbe571249afb1165333a7e9d
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