Instructions to use ai4bharat/IndicBERT-MLM-Wiki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai4bharat/IndicBERT-MLM-Wiki with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ai4bharat/IndicBERT-MLM-Wiki")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ai4bharat/IndicBERT-MLM-Wiki") model = AutoModel.from_pretrained("ai4bharat/IndicBERT-MLM-Wiki") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef1798efecf9731e81a05b63fb1b3030a81f36e7871a587dda3e419255b2f6b6
- Size of remote file:
- 1.11 GB
- SHA256:
- 5c3e6f364b31619124e85cd1e808bd30fd1a4477336ba787a549074715a05581
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.