Instructions to use ai4bharat/IndicBERTv2-MLM-only-QA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai4bharat/IndicBERTv2-MLM-only-QA with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="ai4bharat/IndicBERTv2-MLM-only-QA")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ai4bharat/IndicBERTv2-MLM-only-QA") model = AutoModelForQuestionAnswering.from_pretrained("ai4bharat/IndicBERTv2-MLM-only-QA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ai4bharat/IndicBERTv2-MLM-only-QA: direct link, hf CLI and curl.
- Browser
- Download file 7.75 MB
-
https://huggingface.co/ai4bharat/IndicBERTv2-MLM-only-QA/resolve/main/tokenizer.json
- Command line
-
hf download hf://ai4bharat/IndicBERTv2-MLM-only-QA/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ai4bharat/IndicBERTv2-MLM-only-QA/resolve/main/tokenizer.json
7.75 MB
- Xet hash:
- e68b96a851194bd0fbeb371df769079c6a0e42624f028ac0aed1d589b5789da1
- Size of remote file:
- 7.75 MB
- SHA256:
- 89e7958222ec35bb7037c2f1383dd5a12ed9f3ab434577f96a5d9c528605c79f
路
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