Instructions to use l3cube-pune/marathi-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/marathi-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="l3cube-pune/marathi-roberta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/marathi-roberta") model = AutoModelForMaskedLM.from_pretrained("l3cube-pune/marathi-roberta", 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 (ba5e4518c67dc8ff15329920563b6da9b2591e81) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>685a057
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Initial commit for MahaRoBERTa model trained on L3Cube-MahaMono Corpus
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