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L3.3-Mokume-Gane-R1-70b-v1.1-mlx-4Bit
Wwayu/L3.3-Mokume-Gane-R1-70b-v1.1-mlx-4Bit
L3.3-Mokume-Gane-R1-70b-v1.1-mlx-4Bit is a machine learning model from Wwayu. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlx. The card lists the license as llama3.3.
The Model Wwayu/L3.3-Mokume-Gane-R1-70b-v1.1-mlx-4Bit was converted to MLX format from Steelskull/L3.3-Mokume-Gane-R1-70b-v1.1 using mlx-lm version 0.26.4.
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70.6B
39.7 GB on disk
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.safetensors39.7 GB · 100%
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How the weights are stored.
U3270.6B · 100%
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Model card
From the Hugging Face model README
Wwayu/L3.3-Mokume-Gane-R1-70b-v1.1-mlx-4Bit
The Model Wwayu/L3.3-Mokume-Gane-R1-70b-v1.1-mlx-4Bit was converted to MLX format from Steelskull/L3.3-Mokume-Gane-R1-70b-v1.1 using mlx-lm version 0.26.4.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("Wwayu/L3.3-Mokume-Gane-R1-70b-v1.1-mlx-4Bit")
prompt="hello"
if hasattr(tokenizer, "apply_chat_template") and tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)
- Library
- mlx
- Type
- llama
- License
- llama3.3
- Created
- Oct 25, 2025
- Updated
- Oct 25, 2025