metadata
library_name: mlx
tags:
- compression
- expert-merging
- moe
- code
- mlx
license: apache-2.0
base_model: SamsungSAILMontreal/Qwen3-Coder-Next-REAP
pipeline_tag: text-generation
jedisct1/Qwen3-Coder-Next-REAP-q4-mlx
This model jedisct1/Qwen3-Coder-Next-REAP-q4-mlx was converted to MLX format from SamsungSAILMontreal/Qwen3-Coder-Next-REAP using mlx-lm version 0.30.7.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("jedisct1/Qwen3-Coder-Next-REAP-q4-mlx")
prompt = "hello"
if tokenizer.chat_template is not None:
messages = [{"role": "user", "content": prompt}]
prompt = tokenizer.apply_chat_template(
messages, add_generation_prompt=True, return_dict=False,
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)