Instructions to use castorini/bpr-nq-question-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use castorini/bpr-nq-question-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="castorini/bpr-nq-question-encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("castorini/bpr-nq-question-encoder") model = AutoModel.from_pretrained("castorini/bpr-nq-question-encoder") - Notebooks
- Google Colab
- Kaggle
Upload pytorch_model.bin with git-lfs
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
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