Instructions to use deepset/gbert-base-germandpr-ctx_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/gbert-base-germandpr-ctx_encoder with Transformers:
# Load model directly from transformers import AutoTokenizer, DPRContextEncoder tokenizer = AutoTokenizer.from_pretrained("deepset/gbert-base-germandpr-ctx_encoder") model = DPRContextEncoder.from_pretrained("deepset/gbert-base-germandpr-ctx_encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepset/gbert-base-germandpr-ctx_encoder: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/deepset/gbert-base-germandpr-ctx_encoder/resolve/5c13387b5f87efc8b2363f86416b2f2d980e19c7/pytorch_model.bin
- Command line
-
hf download hf://deepset/gbert-base-germandpr-ctx_encoder@5c13387b5f87efc8b2363f86416b2f2d980e19c7/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/gbert-base-germandpr-ctx_encoder/resolve/5c13387b5f87efc8b2363f86416b2f2d980e19c7/pytorch_model.bin
440 MB
- Xet hash:
- d67b51dcfcb1ce063ec01da640a1663322b06b2cbffd838019194813c0a7af1a
- Size of remote file:
- 440 MB
- SHA256:
- 81027779cf0b4e3fea7843b6513ba80b1220346f43ea6ce783292734d5f4496c
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