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
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# Marathi-Bloom-560m is a Bloom fine-tuned model trained by ScriptEdge on MahaNLP tweets dataset from L3Cube-MahaNLP.
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## Worked on by
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- Venkatesh Soni.
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- Rayansh Srivastava.
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- Akshay Ugale, Madhukar Alhat.
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## Usage -
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# Marathi-Bloom-560m is a Bloom fine-tuned model trained by ScriptEdge on MahaNLP tweets dataset from L3Cube-MahaNLP.
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## Worked on by:
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-Trained by:
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- Venkatesh Soni.
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-Assistance:
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- Rayansh Srivastava.
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-Supervision:
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- Akshay Ugale, Madhukar Alhat.
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## Usage -
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