Instructions to use mathigatti/vllm-instruct-prices-description with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mathigatti/vllm-instruct-prices-description with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mathigatti/vllm-instruct-prices-description", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecd6a4a9818a0cfa9830ae42894a9798c43f55906badc306461d09d596e5d73a
- Size of remote file:
- 5.75 kB
- SHA256:
- ccd51c200f012d5ed3d95b428a5adbcdca86b2139b4bb1dbb0141cdac14ac16f
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