Instructions to use facebook/dpr-ctx_encoder-multiset-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dpr-ctx_encoder-multiset-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, DPRContextEncoder tokenizer = AutoTokenizer.from_pretrained("facebook/dpr-ctx_encoder-multiset-base") model = DPRContextEncoder.from_pretrained("facebook/dpr-ctx_encoder-multiset-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add model card
Hi! This PR has a preliminary model card, based on the format we are using as part of our effort to standardize model cards at Hugging Face. It is very similar to the proposed model card at https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/discussions/1 Feel free to merge if you are ok with the changes! (cc @Ezi @Meg @Nazneen)c27f75c
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Add tokenizer config
Thomas Wolf6c01adf -
Add vocab
Thomas Wolfdf99472
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Adding TensorFlow checkpoint
d26ecd0
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Update config.json
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Update pytorch_model.bin
6a3d89c -
initial commit
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