Instructions to use mlc-ai/gemma-3-1b-it-q4f16_1-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-q4f16_1-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_1.bin from mlc-ai/gemma-3-1b-it-q4f16_1-MLC: direct link, hf CLI and curl.
- Browser
- Download file 33.2 MB
-
https://huggingface.co/mlc-ai/gemma-3-1b-it-q4f16_1-MLC/resolve/304745e3dc457b89f88dbcd36698b36433ad3fef/params_shard_1.bin
- Command line
-
hf download hf://mlc-ai/gemma-3-1b-it-q4f16_1-MLC@304745e3dc457b89f88dbcd36698b36433ad3fef/params_shard_1.bin
-
curl -L -o params_shard_1.bin https://huggingface.co/mlc-ai/gemma-3-1b-it-q4f16_1-MLC/resolve/304745e3dc457b89f88dbcd36698b36433ad3fef/params_shard_1.bin
33.2 MB
- Xet hash:
- 5fcd3d8eb2bd0c2a14e84a4fddb210567651ed477b2c358786e20223fe4c4ec4
- Size of remote file:
- 33.2 MB
- SHA256:
- 1095155c03dcc30780380dbe51c07e5e6138f4927900c0e6d0d6ae5b19c28a0b
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