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:
- 462151f83e60f19f14329872db160dc7ac927cc650cf2b1f3a5495464694dffb
- Size of remote file:
- 165 MB
- SHA256:
- 1b927a007e3bcd0c28a78be2f640b7496883ca7366c72a8ba6f93efbc889577d
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