Instructions to use jvelja/vllm-gemma2b-stringMatcher-newDataset_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jvelja/vllm-gemma2b-stringMatcher-newDataset_3 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jvelja/vllm-gemma2b-stringMatcher-newDataset_3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8fb8fb6f98b67166bdd55328ba703ab2bf26123a2d9ce47c2ce93b5b9c5b76b4
- Size of remote file:
- 10.7 kB
- SHA256:
- b7fb6725ca03988fb3156a419ad1205110ab3c58ca493649d8e5b92fca0b8155
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