Instructions to use l3cube-pune/hing-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/hing-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="l3cube-pune/hing-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/hing-bert") model = AutoModelForMaskedLM.from_pretrained("l3cube-pune/hing-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#2)
- Adding `safetensors` variant of this model (e552793585fa29a4421578fa1b85db3fbbcb38cf) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>be2699e
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initial commit
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