nightmedia/Qwen3.5-122B-A10B-Text-mxfp4-mlx

🤗 Hugging Face 来源text-generationapache-2.0122B 参数激活 10B244 GBsafetensors✓ 14 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo nightmedia/Qwen3.5-122B-A10B-Text-mxfp4-mlx ./model-folder
需要做种者 →

Qwen3.5-122B-A10B-Text-mxfp4-mlx

This model is Text only, the vision tower was removed.

Brainwaves

           arc arc/e
qx85     0.456,0.519,0.622,0.704,0.392,0.774,0.680
qx64-hi  0.445,0.513,0.622,0.704,0.384,0.786,0.702
mxfp4    0.455,0.510,0.621,...

Quant    Perplexity     Speed(t/s)  Memory
qx85     3.762 ± 0.024  448         98.86 GB
qx64-hi  3.778 ± 0.024  435         98.28 GB
mxfp4    3.909 ± 0.025  535         71.94 GB

-G

This model Qwen3.5-122B-A10B-Text-mxfp4-mlx was converted to MLX format from Qwen/Qwen3.5-122B-A10B using mlx-lm version 0.30.8.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("Qwen3.5-122B-A10B-Text-mxfp4-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)