Instructions to use dawncr0w/Hy-MT2-30B-A3B-oQ4-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use dawncr0w/Hy-MT2-30B-A3B-oQ4-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Hy-MT2-30B-A3B-oQ4-MLX dawncr0w/Hy-MT2-30B-A3B-oQ4-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Hy-MT2-30B-A3B-oQ4-MLX
This is an oQ4 MLX quantized derivative of tencent/Hy-MT2-30B-A3B.
The model was quantized locally with oMLX oQ4. The resulting config targets approximately 4.62 bpw and includes a packaged hy_v3.py model file so MLX-LM can load the HYV3 architecture from the model directory.
Validation
Local validation completed with the oMLX app bundle on macOS:
mlx_lm load: passed
generation smoke test: passed
prompt: Hello
max tokens: 4
peak memory: 17.435 GB
Usage
Use an MLX-LM build that supports the APIs used by the packaged hy_v3.py file.
python -m mlx_lm generate \
--model /path/to/Hy-MT2-30B-A3B-oQ4-MLX \
--ignore-chat-template \
--prompt "Hello" \
--max-tokens 32 \
--temp 0
License And Notice
The base model is distributed under the Tencent HY Community License Agreement. This distribution includes LICENSE.txt and NOTICE from/for the Tencent HY license requirements.
This repository is not affiliated with, sponsored by, or endorsed by Tencent.
- Downloads last month
- 62
4-bit
Model tree for dawncr0w/Hy-MT2-30B-A3B-oQ4-MLX
Base model
tencent/Hy-MT2-30B-A3B