Instructions to use castorini/mdpr-question-nq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use castorini/mdpr-question-nq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="castorini/mdpr-question-nq")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("castorini/mdpr-question-nq") model = AutoModel.from_pretrained("castorini/mdpr-question-nq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a91ac9716e790760425fd02c5ebad40b8940b9ee1e4650177be79af5f54f8253
- Size of remote file:
- 711 MB
- SHA256:
- dcf35526a8539a1d8a3db062841c1e42ce42a3e92d82eef22095377494420d3f
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