93 lines
2.9 KiB
Python
93 lines
2.9 KiB
Python
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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Whisper 模型离线下载工具
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用于在有网络的机器上下载模型，然后复制到内网服务器
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使用方法：
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1. 在有网络的机器上运行此脚本
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2. 将下载的模型文件复制到服务器
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3. 放到指定目录：~/.cache/whisper/ (Linux) 或 C:\Users\用户名\.cache\whisper\ (Windows)
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"""
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import whisper
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import os
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import shutil
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def download_model(model_name="base"):
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"""
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下载 Whisper 模型
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可选模型：
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- tiny: 39M, 最快，准确度一般
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- base: 74M, 快速，准确度好 ✅ 推荐
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- small: 244M, 较慢，准确度高
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- medium: 769M, 很慢，准确度很高
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- large: 1550M, 非常慢，准确度最高
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"""
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print("=" * 60)
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print(f" 下载 Whisper {model_name} 模型")
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print("=" * 60)
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print("")
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print(f"[1/2] 开始下载模型：{model_name}...")
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print("⏳ 请耐心等待，根据网络速度可能需要几分钟...")
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try:
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model = whisper.load_model(model_name)
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print(f"✅ 模型下载成功！")
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print("")
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# 获取模型路径
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import whisper
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cache_dir = os.path.join(os.path.expanduser("~"), ".cache", "whisper")
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model_file = os.path.join(cache_dir, f"{model_name}.pt")
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print("[2/2] 模型文件信息：")
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print(f" 路径: {model_file}")
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if os.path.exists(model_file):
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size = os.path.getsize(model_file) / (1024 * 1024)
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print(f" 大小: {size:.1f} MB")
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print("")
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print("=" * 60)
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print("📝 后续步骤（内网部署）：")
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print("=" * 60)
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print(f"1. 复制模型文件到服务器：")
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print(f" scp {model_file} user@server:~/.cache/whisper/")
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print("")
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print(f"2. Windows 服务器路径：")
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print(f" C:\\Users\\用户名\\.cache\\whisper\\{model_name}.pt")
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print("")
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print(f"3. Linux 服务器路径：")
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print(f" ~/.cache/whisper/{model_name}.pt")
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print("")
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print("✅ 完成！")
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except Exception as e:
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print(f"❌ 下载失败：{e}")
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print("")
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print("💡 解决方法：")
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print("1. 检查网络连接")
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print("2. 尝试使用代理")
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print("3. 手动下载：https://openaipublic.azureedge.net/main/whisper/models/")
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if __name__ == '__main__':
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import sys
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# 支持命令行参数指定模型
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model_name = sys.argv[1] if len(sys.argv) > 1 else "base"
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print("")
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print("📦 Whisper 模型下载工具")
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print("")
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print("可用模型：")
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print(" tiny - 39M (最快，准确度一般)")
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print(" base - 74M (推荐，快速且准确) ✅")
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print(" small - 244M (准确度高)")
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print(" medium - 769M (准确度很高)")
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print(" large - 1550M (准确度最高)")
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print("")
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download_model(model_name)
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