Instructions to use Archeops/dpr-trail_passage_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Archeops/dpr-trail_passage_encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Archeops/dpr-trail_passage_encoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Archeops/dpr-trail_passage_encoder") model = AutoModel.from_pretrained("Archeops/dpr-trail_passage_encoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Archeops/dpr-trail_passage_encoder: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/Archeops/dpr-trail_passage_encoder/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Archeops/dpr-trail_passage_encoder@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Archeops/dpr-trail_passage_encoder/resolve/refs%2Fpr%2F1/pytorch_model.bin
438 MB
- Xet hash:
- 2c032aed51476a4ce0429c9718de7c6307ec09348c2f2840349f439d6294253f
- Size of remote file:
- 438 MB
- SHA256:
- a4230bb2cd40162f3b35b33496cd450a398001ac2aa4000459b9da2bbfd7f6ad
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