metadata
license: apache-2.0
language:
- en
- code
library_name: transformers
tags:
- causal-lm
- moe
- mixture-of-experts
- qwen
- distillation
- svd
- lora-merged
- code-generation
- mlx
- mlx-my-repo
- mlx
- mlx-my-repo
base_model: YOYO-AI/Qwen3-Coder-30B-A3B-Instruct-480B-Distill-V2-Fp32-mlx-fp16
introvoyz041/Qwen3-Coder-30B-A3B-Instruct-480B-Distill-V2-Fp32-mlx-fp16-mlx-4Bit
The Model introvoyz041/Qwen3-Coder-30B-A3B-Instruct-480B-Distill-V2-Fp32-mlx-fp16-mlx-4Bit was converted to MLX format from YOYO-AI/Qwen3-Coder-30B-A3B-Instruct-480B-Distill-V2-Fp32-mlx-fp16 using mlx-lm version 0.28.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("introvoyz041/Qwen3-Coder-30B-A3B-Instruct-480B-Distill-V2-Fp32-mlx-fp16-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)