Instructions to use welcoma/Bonsai-1.7B-bonsai_q1_f32-MLC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use welcoma/Bonsai-1.7B-bonsai_q1_f32-MLC with MLC-LLM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc538930a5599977ce04f9f5dd0bd2f27d5a57e32b56daa93015cc83006d640f
- Size of remote file:
- 33.3 MB
- SHA256:
- 310450d1ad1ef12fe36459e58caa0deff91de0dff1dbcbdbc1b799f840c99a8e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.