Text Generation
MLC-LLM
Japanese
English
Chinese
gemma3
transformer
instruction-tuned
multilingual
uncensored
non-censored
unfiltered
web-llm
conversational
Instructions to use kawasumi/Tema_Q-R-4B-MLC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLC-LLM
How to use kawasumi/Tema_Q-R-4B-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_39.bin from kawasumi/Tema_Q-R-4B-MLC: direct link, hf CLI and curl.
- Browser
- Download file 26.2 MB
-
https://huggingface.co/kawasumi/Tema_Q-R-4B-MLC/resolve/main/params_shard_39.bin
- Command line
-
hf download hf://kawasumi/Tema_Q-R-4B-MLC/params_shard_39.bin
-
curl -L -o params_shard_39.bin https://huggingface.co/kawasumi/Tema_Q-R-4B-MLC/resolve/main/params_shard_39.bin
26.2 MB
- Xet hash:
- f503cf10ef075bb9b5cbcf3cd453879d9c0d095372d8380a91ddebb9c3c3bc35
- Size of remote file:
- 26.2 MB
- SHA256:
- 6c5f424616a04b28e60175aeb9ba758223a5ad1f315a21adffa73113ed753e20
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.