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:
- 205be3fe12bd09f48008f550229ddd06f2b2aae85921b9ac79c5ce78fcb85d4a
- Size of remote file:
- 90.9 MB
- SHA256:
- 0f1f3118c0dea1899c37924c337d2139e9d7740fea718416c5553c6b7a74ec22
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