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:
- 7c0141e08f83f185544db94f663381b6493f008320f971b07ec4f38150fa531b
- Size of remote file:
- 82.5 MB
- SHA256:
- a07e0adb07bf671bff07bbd134f54b91bddcfee0950f1a9fc501e361c62890a4
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