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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84fb2f8ef6d4b209a6dd95e63e8eb1615763dc7e3d2458dfc3d50a55d02fa331
- Size of remote file:
- 90.9 MB
- SHA256:
- e67cd33989d5633a4ffae5726dafee6d4fd3f42b9f888315746b50c64c9814a0
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