Instructions to use mlc-ai/gemma-3-1b-it-q0f32-MLC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use mlc-ai/gemma-3-1b-it-q0f32-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
Download params_shard_14.bin from mlc-ai/gemma-3-1b-it-q0f32-MLC: direct link, hf CLI and curl.
- Browser
- Download file 21.8 MB
-
https://huggingface.co/mlc-ai/gemma-3-1b-it-q0f32-MLC/resolve/c8ab88d587a2599da367ad3dfac1f423f98f4e9b/params_shard_14.bin
- Command line
-
hf download hf://mlc-ai/gemma-3-1b-it-q0f32-MLC@c8ab88d587a2599da367ad3dfac1f423f98f4e9b/params_shard_14.bin
-
curl -L -o params_shard_14.bin https://huggingface.co/mlc-ai/gemma-3-1b-it-q0f32-MLC/resolve/c8ab88d587a2599da367ad3dfac1f423f98f4e9b/params_shard_14.bin
21.8 MB
- Xet hash:
- a4c1c915fe8d59e008191383a1ea049be2ddc24314e891bf742d04680622a6d9
- Size of remote file:
- 21.8 MB
- SHA256:
- f04e5eddddbbcd82466249c2dd5c46e01df023a251c7f5b35e1e574ba9041249
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