Instructions to use vespa-engine/col-minilm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vespa-engine/col-minilm with Transformers:
# Load model directly from transformers import AutoTokenizer, ColBERT tokenizer = AutoTokenizer.from_pretrained("vespa-engine/col-minilm") model = ColBERT.from_pretrained("vespa-engine/col-minilm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b67a1b8406d46493b41a95700b3322ef2438c716cb3cafa4c4fae4ccf680e3ea
- Size of remote file:
- 41.6 MB
- SHA256:
- 4205140dcb2f8b2135bc9f848f1ea09865c58c839afa6e31aafc48dcca9fb547
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