metadata
license: apache-2.0
library_name: mlx
language:
- en
- fr
- zh
- de
tags:
- programming
- code generation
- code
- codeqwen
- chat
- qwen
- qwen-coder
- moe
- coding
- coder
- qwen2
- mixture of experts
- 128 experts
- 8 active experts
- bfloat16
- qwen3
- finetune
- thinking
- reasoning
- qwen3_moe
- mlx
base_model: DavidAU/Qwen3-53B-A3B-TOTAL-RECALL-MASTER-CODER-v1.4
pipeline_tag: text-generation
nightmedia/Qwen3-53B-A3B-TOTAL-RECALL-MASTER-CODER-v1.4-q6-mlx
This model nightmedia/Qwen3-53B-A3B-TOTAL-RECALL-MASTER-CODER-v1.4-q6-mlx was converted to MLX format from DavidAU/Qwen3-53B-A3B-TOTAL-RECALL-MASTER-CODER-v1.4 using mlx-lm version 0.25.3.
Use with mlx
pip install mlx-lm
from mlx_lm import load, generate
model, tokenizer = load("nightmedia/Qwen3-53B-A3B-TOTAL-RECALL-MASTER-CODER-v1.4-q6-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
)
response = generate(model, tokenizer, prompt=prompt, verbose=True)