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")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ai4bharat/IndicBERTv2-MLM-only") model = AutoModelForMaskedLM.from_pretrained("ai4bharat/IndicBERTv2-MLM-only") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a29a0f06a4d8739d74b852fb4cb8dc4969f881085bd0e221c854231a5c6732d
- Size of remote file:
- 7.75 MB
- SHA256:
- 6af22a5c4bc890322c365fcb77dd77c06cbb9b088ffa50db1892d5220313c495
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