Instructions to use stdlogits/drowse-web-gemma3-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use stdlogits/drowse-web-gemma3-4b 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 model.wasm from stdlogits/drowse-web-gemma3-4b: direct link, hf CLI and curl.
- Browser
- Download file 37.6 MB
-
https://huggingface.co/stdlogits/drowse-web-gemma3-4b/resolve/main/model.wasm
- Command line
-
hf download hf://stdlogits/drowse-web-gemma3-4b/model.wasm
-
curl -L -o model.wasm https://huggingface.co/stdlogits/drowse-web-gemma3-4b/resolve/main/model.wasm
37.6 MB
- Xet hash:
- a07fe4f95388125804e6523c0531386221694db97369480ea16ca4993bfd71ce
- Size of remote file:
- 37.6 MB
- SHA256:
- 03f371d57997e461cf7668486dd028e53f7f1276cc5e6fcf5581c48b462f6bd8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.