---
license: apache-2.0
language:
- zh
- en
library_name: mlx
---

# BiliBot

b友风格聊天机器人

+ 基础模型: Qwen2-7B
+ 数据来源: [https://github.com/linyiLYi/bilibot/tree/main/data](https://github.com/linyiLYi/bilibot/tree/main/data)
+ 量化: 4bit
+ 推荐配置: 16G内存及以上的M系芯片Macbook

> 由于是MLX格式模型，首先需要安装 mlx-lm 包

```bash
pip install mlx-lm
``` 

下面是一个示例，用户可随意提问

```python
import time
from mlx_lm import load, generate

model, tokenizer = load('Kadins/BiliBot-Qwen2-7B-Q-FT', tokenizer_config={"eos_token": "<|im_end|>"})

# Template content
template = """
<|im_start|>system
You are a helpful assistant<|im_end|>
<|im_start|>user
你是一位B站老用户，请你对以下问题给出简短、机智的回答：
{usr_msg}<|im_end|>
<|im_start|>assistant
"""

while True:
    usr_msg = input("用户: ")  # Get user message from terminal
    if usr_msg.lower() == 'quit()':  # Allows the user to exit the loop
        break

    prompt = template.replace("{usr_msg}", usr_msg)

    time_ckpt = time.time()
    response = generate(
        model,
        tokenizer,
        prompt=prompt,
        temp=0.3,
        max_tokens=500,
        verbose=False
    )

    print("%s: %s (Time %d ms)\n" % ("回答", response, (time.time() - time_ckpt) * 1000))
```