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:
# 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
Download tf_model.h5 from facebook/dpr-ctx_encoder-multiset-base: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/6c01adf9e9e7c812c0fa998fed97eec3262c2cf4/tf_model.h5
- Command line
-
hf download hf://facebook/dpr-ctx_encoder-multiset-base@6c01adf9e9e7c812c0fa998fed97eec3262c2cf4/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/facebook/dpr-ctx_encoder-multiset-base/resolve/6c01adf9e9e7c812c0fa998fed97eec3262c2cf4/tf_model.h5
438 MB
- Xet hash:
- e25f41017e41646438d529239157c5b608b9aaf52f4a28081237138b217e8014
- Size of remote file:
- 438 MB
- SHA256:
- c5783e8d68dfac813126370a9c3e75889d0e544ed47423dc50fea6e247b31346
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