Instructions to use castorini/bpr-nq-ctx-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use castorini/bpr-nq-ctx-encoder with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, DPRContextEncoder tokenizer = AutoTokenizer.from_pretrained("castorini/bpr-nq-ctx-encoder") model = DPRContextEncoder.from_pretrained("castorini/bpr-nq-ctx-encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload pytorch_model.bin with git-lfs
Upload pytorch_model.binc905ce7 -
Upload vocab.txt
Upload vocab.txtac3eb82 -
Upload tokenizer_config.json
Upload tokenizer_config.json4d7c224 -
Upload tokenizer.json
Upload tokenizer.jsonbd35ef1 -
Upload config.json
Upload config.json5b0e318 -
Create README.md
3b692ab -
initial commit
3d1c724