Instructions to use PPeSse/WhiteRabbitNeo-v2-q4f32-transcoded-MLC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use PPeSse/WhiteRabbitNeo-v2-q4f32-transcoded-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_4.bin from PPeSse/WhiteRabbitNeo-v2-q4f32-transcoded-MLC: direct link, hf CLI and curl.
- Browser
- Download file 32.8 MB
-
https://huggingface.co/PPeSse/WhiteRabbitNeo-v2-q4f32-transcoded-MLC/resolve/main/params_shard_4.bin
- Command line
-
hf download hf://PPeSse/WhiteRabbitNeo-v2-q4f32-transcoded-MLC/params_shard_4.bin
-
curl -L -o params_shard_4.bin https://huggingface.co/PPeSse/WhiteRabbitNeo-v2-q4f32-transcoded-MLC/resolve/main/params_shard_4.bin
32.8 MB
- Xet hash:
- e87cb2364b5c0606d965056f45908a2dbf0291e19198c81abcf4d4dedf282e71
- Size of remote file:
- 32.8 MB
- SHA256:
- 08c3ad22cc9399ebdbe73c5640149725b6621652e79eb004572236b902b4633b
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