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 params_shard_14.bin from stdlogits/drowse-web-gemma3-4b: direct link, hf CLI and curl.
- Browser
- Download file 31.6 MB
-
https://huggingface.co/stdlogits/drowse-web-gemma3-4b/resolve/main/params_shard_14.bin
- Command line
-
hf download hf://stdlogits/drowse-web-gemma3-4b/params_shard_14.bin
-
curl -L -o params_shard_14.bin https://huggingface.co/stdlogits/drowse-web-gemma3-4b/resolve/main/params_shard_14.bin
31.6 MB
- Xet hash:
- f871080739ce6b9b4f6e4b3b179e119f2d02391729f664bbc6058fdd14624cef
- Size of remote file:
- 31.6 MB
- SHA256:
- e32c3a5289bb2017ee057e56c3c990546d455b7c4092579ccf0d0b4d52139b2b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.