Instructions to use l3cube-pune/hindi-roberta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/hindi-roberta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="l3cube-pune/hindi-roberta")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/hindi-roberta") model = AutoModelForMaskedLM.from_pretrained("l3cube-pune/hindi-roberta") - Notebooks
- Google Colab
- Kaggle
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README.md
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<a href='https://huggingface.co/l3cube-pune/gujarati-bert'> Gujarati BERT </a> <br>
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<a href='https://huggingface.co/l3cube-pune/odia-bert'> Oriya BERT </a> <br>
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<a href='https://huggingface.co/l3cube-pune/bengali-bert'> Bengali BERT </a> <br>
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<a href='https://huggingface.co/l3cube-pune/punjabi-bert'> Punjabi BERT </a> <br>
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<a href='https://huggingface.co/l3cube-pune/gujarati-bert'> Gujarati BERT </a> <br>
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<a href='https://huggingface.co/l3cube-pune/odia-bert'> Oriya BERT </a> <br>
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<a href='https://huggingface.co/l3cube-pune/bengali-bert'> Bengali BERT </a> <br>
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<a href='https://huggingface.co/l3cube-pune/punjabi-bert'> Punjabi BERT </a> <br>
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<a href='https://huggingface.co/l3cube-pune/assamese-bert'> Assamese BERT </a> <br>
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