Downloads · 30 days
139
3% of all-time downloads
mrtoots/unsloth-Qwen3-Coder-30B-A3B-Instruct-mlx-8Bit
unsloth-Qwen3-Coder-30B-A3B-Instruct-mlx-8Bit is a text generation model from mrtoots. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as apache-2.0.
The Model huggingtoots/unsloth-Qwen3-Coder-30B-A3B-Instruct-mlx-8Bit was converted to MLX format from unsloth/Qwen3-Coder-30B-A3B-Instruct using mlx-lm version 0.26.4.
Downloads · 30 days
139
3% of all-time downloads
All-time downloads
4.1K
Public
Parameters
30.5B
32.5 GB on disk
Likes
0
Public
Click a slice to open those files.
.safetensors32.4 GB · 100%
How the weights are stored.
U3230.5B · 100%
From the Hugging Face model README
The Model huggingtoots/unsloth-Qwen3-Coder-30B-A3B-Instruct-mlx-8Bit was converted to MLX format from unsloth/Qwen3-Coder-30B-A3B-Instruct using mlx-lm version 0.26.4.
This model was converted and quantized utilizing unsloth's version of Qwen3-Coder-30B-A3B-Instruct. Should include the chat template fixes.
Please follow and support unsloth's work if you like it!
🦛 <span style="color:#800080">If you want a free consulting session, </span>fill out this form <span style="color:#800080">to get in touch!</span> 🤗
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("huggingtoots/Qwen3-Coder-30B-A3B-Instruct-mlx-8Bit")
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)