Instructions to use ai4bharat/IndicBERTv2-MLM-only with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai4bharat/IndicBERTv2-MLM-only with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ai4bharat/IndicBERTv2-MLM-only")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ai4bharat/IndicBERTv2-MLM-only") model = AutoModelForMaskedLM.from_pretrained("ai4bharat/IndicBERTv2-MLM-only", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ai4bharat/IndicBERTv2-MLM-only: direct link, hf CLI and curl.
- Browser
- Download file 1.12 GB
-
https://huggingface.co/ai4bharat/IndicBERTv2-MLM-only/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ai4bharat/IndicBERTv2-MLM-only/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ai4bharat/IndicBERTv2-MLM-only/resolve/main/pytorch_model.bin
1.12 GB
- Xet hash:
- c9cefd6121ad1bfcf25e556cd35a09f691b2d855b2129bd5cd49ba7225b182dd
- Size of remote file:
- 1.12 GB
- SHA256:
- 6c2f5914e66cbf590f0a472a3b3d89f866885dc42296e73ffcb2186c147ece56
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