Instructions to use mlc-ai/gemma-3-27b-it-q4bf16_0-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-q4bf16_0-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_128.bin from mlc-ai/gemma-3-27b-it-q4bf16_0-MLC: direct link, hf CLI and curl.
- Browser
- Download file 57.8 MB
-
https://huggingface.co/mlc-ai/gemma-3-27b-it-q4bf16_0-MLC/resolve/5d346a4a05c0a5c571ff2f31d91b5d26bf4b9cd8/params_shard_128.bin
- Command line
-
hf download hf://mlc-ai/gemma-3-27b-it-q4bf16_0-MLC@5d346a4a05c0a5c571ff2f31d91b5d26bf4b9cd8/params_shard_128.bin
-
curl -L -o params_shard_128.bin https://huggingface.co/mlc-ai/gemma-3-27b-it-q4bf16_0-MLC/resolve/5d346a4a05c0a5c571ff2f31d91b5d26bf4b9cd8/params_shard_128.bin
57.8 MB
- Xet hash:
- afa6c7197cfd0ff10d89efeda6d4295423e9781568c4a536c50ea583c2c48aa7
- Size of remote file:
- 57.8 MB
- SHA256:
- 26d4e21722e2189fc9c83518ddf691d2ffb45ad100df4917c1b265280ba38294
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