WaveCut/Qwen_Qwen2.5-14B-Instruct-1M_MLX-4bit

🤗 Hugging Face 来源text-generationapache-2.014.8B 参数30 GBsafetensors✓ 3 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 WaveCut/Qwen_Qwen2.5-14B-Instruct-1M_MLX-4bit ./model-folder
需要做种者 →

WaveCut/Qwen_Qwen2.5-14B-Instruct-1M_MLX-4bit

The Model WaveCut/Qwen_Qwen2.5-14B-Instruct-1M_MLX-4bit was converted to MLX format from Qwen/Qwen2.5-14B-Instruct-1M using mlx-lm version 0.21.1.

Use with mlx

pip install mlx-lm
from mlx_lm import load, generate

model, tokenizer = load("WaveCut/Qwen_Qwen2.5-14B-Instruct-1M_MLX-4bit")

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)