Instructions to use vespa-engine/colbert-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vespa-engine/colbert-medium with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, ColBERT tokenizer = AutoTokenizer.from_pretrained("vespa-engine/colbert-medium") model = ColBERT.from_pretrained("vespa-engine/colbert-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from vespa-engine/colbert-medium: direct link, hf CLI and curl.
- Browser
- Download file 166 MB
-
https://huggingface.co/vespa-engine/colbert-medium/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://vespa-engine/colbert-medium@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vespa-engine/colbert-medium/resolve/refs%2Fpr%2F2/pytorch_model.bin
166 MB
- Xet hash:
- 34f4ac504739a8ad8c41cdfa337211583a223201698d6c60e20ad3bc75c81d50
- Size of remote file:
- 166 MB
- SHA256:
- 15f33bb114e0f9ae177e2eedddd880170300957ddecd2352fd17bda3e6719bd6
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