Instructions to use mlc-ai/gemma-3-27b-it-q0bf16-MLC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use mlc-ai/gemma-3-27b-it-q0bf16-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_100.bin from mlc-ai/gemma-3-27b-it-q0bf16-MLC: direct link, hf CLI and curl.
- Browser
- Download file 44 MB
-
https://huggingface.co/mlc-ai/gemma-3-27b-it-q0bf16-MLC/resolve/92e970609dd13dbba6714322200f01190c27ecfe/params_shard_100.bin
- Command line
-
hf download hf://mlc-ai/gemma-3-27b-it-q0bf16-MLC@92e970609dd13dbba6714322200f01190c27ecfe/params_shard_100.bin
-
curl -L -o params_shard_100.bin https://huggingface.co/mlc-ai/gemma-3-27b-it-q0bf16-MLC/resolve/92e970609dd13dbba6714322200f01190c27ecfe/params_shard_100.bin
44 MB
- Xet hash:
- 997daf837a96a17b5d9941f30858c93850337fba0d44f9e3585eba7ccb3e4227
- Size of remote file:
- 44 MB
- SHA256:
- 4f40727de772da7848ab91fa7309eab07ca60c88adc4e86b22320bd147e631b9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.