Instructions to use mchl-labs/stambecco-7b-plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mchl-labs/stambecco-7b-plus with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mchl-labs/stambecco-7b-plus", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff24083bb56720e32eef93ffa84b389a83a2d1222705bca2ef1abb8b54bae2ad
- Size of remote file:
- 16.8 MB
- SHA256:
- 02184cb0385798f53ebcaf49c5c145de018f0a977fff353d2b776ab9e346bb0d
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