Instructions to use selcukkubur/Confucius4-R2T2-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use selcukkubur/Confucius4-R2T2-mlx-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir Confucius4-R2T2-mlx-4bit selcukkubur/Confucius4-R2T2-mlx-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Confucius4-R2T2, MLX 4-bit
netease-youdao/Confucius4-R2T2
converted to MLX and quantised to 4 bits (group size 64, affine), for Apple
Silicon. 4.09 GB of bfloat16 becomes 1.5 GB.
Converted with mlx-audio 0.3.1:
python -m mlx_audio.convert --hf-path netease-youdao/Confucius4-R2T2 \
--mlx-path Confucius4-R2T2-mlx-4bit \
-q --q-group-size 64 --q-bits 4 --model-domain stt
The architecture is unchanged — Qwen3ASRForConditionalGeneration, the same one
Qwen/Qwen3-ASR-1.7B uses — so it loads through existing Qwen3-ASR paths in
both mlx-audio and mlx-audio-swift with no custom code.
Use
from mlx_audio.stt.utils import load_model, load_audio
model = load_model("selcukkubur/Confucius4-R2T2-mlx-4bit")
print(model.generate(load_audio("audio.wav")).text)
Notice
Any modifications made to the original model in this Derivative Work are not endorsed, warranted, or guaranteed by the original right-holder of the original model, and the original right-holder disclaims all liability related to this Derivative Work.
This is a quantisation of NetEase Youdao's Confucius4-R2T2 and is governed by the original MODEL_LICENSE. That licence is royalty-free for most users but requires a separate licence from NetEase Youdao above 100 million monthly active users or RMB 1 billion in annual revenue, and prohibits use in the high-risk scenarios it lists. Read it before use.
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