Instructions to use l3cube-pune/marathi-topic-all-doc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/marathi-topic-all-doc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="l3cube-pune/marathi-topic-all-doc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/marathi-topic-all-doc") model = AutoModelForSequenceClassification.from_pretrained("l3cube-pune/marathi-topic-all-doc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (2556ead06827d17ca9d9a6dae6aa9919956c6fe1) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>2bb0949
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