File size: 5,073 Bytes
1de6491 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
将本地 DiffAM 文件夹中的所有内容上传到 Hugging Face Model Repository：
本地目录：
/Users/gaobj/Downloads/DiffAM
目标仓库：
https://huggingface.co/bingjie/DiffAM
安装依赖：
pip install -U huggingface_hub
运行前设置 Token：
export HF_TOKEN="你的新HuggingFaceToken"
运行：
python upload_diffam_to_huggingface.py
"""
import os
import sys
from pathlib import Path
from huggingface_hub import HfApi
from huggingface_hub.errors import HfHubHTTPError
# ============================================================
# 配置
# ============================================================
LOCAL_FOLDER = Path("/Users/gaobj/Downloads/DiffAM")
# Hugging Face 模型仓库格式为：用户名/仓库名
REPO_ID = "bingjie/DiffAM"
# 可选：
# False：公开仓库
# True：私有仓库
PRIVATE_REPO = False
COMMIT_MESSAGE = "Upload DiffAM model files"
def get_hf_token() -> str:
"""
从环境变量读取 Hugging Face Access Token。
"""
token = os.environ.get("HF_TOKEN")
if not token:
raise RuntimeError(
"没有找到环境变量 HF_TOKEN。\n\n"
"请先在终端执行：\n"
'export HF_TOKEN="你的HuggingFaceAccessToken"\n\n'
"然后重新运行此脚本。"
)
return token.strip()
def check_local_folder(folder: Path) -> None:
"""
检查本地目录是否存在且不为空。
"""
if not folder.exists():
raise FileNotFoundError(f"本地目录不存在：{folder}")
if not folder.is_dir():
raise NotADirectoryError(f"该路径不是文件夹：{folder}")
files = [path for path in folder.rglob("*") if path.is_file()]
if not files:
raise RuntimeError(f"本地目录为空，没有可上传的文件：{folder}")
total_size = sum(path.stat().st_size for path in files)
print(f"本地目录：{folder}")
print(f"文件数量：{len(files)}")
print(f"文件总大小：{format_size(total_size)}")
def format_size(size_bytes: int) -> str:
"""
将字节数转换为便于阅读的格式。
"""
size = float(size_bytes)
for unit in ["B", "KB", "MB", "GB", "TB"]:
if size < 1024 or unit == "TB":
return f"{size:.2f} {unit}"
size /= 1024
return f"{size_bytes} B"
def upload_folder() -> None:
"""
创建 Hugging Face 模型仓库，并上传整个本地文件夹。
"""
check_local_folder(LOCAL_FOLDER)
token = get_hf_token()
api = HfApi(token=token)
try:
# 验证 Token，并获取当前账户信息
user_info = api.whoami()
username = user_info.get("name", "unknown")
print(f"当前 Hugging Face 账户：{username}")
if username != "bingjie":
print(
f"警告：当前 Token 所属账户是 {username}，"
f"但目标仓库位于 bingjie 名下。"
)
# 创建仓库；exist_ok=True 表示仓库已存在时不会报错
repo_url = api.create_repo(
repo_id=REPO_ID,
repo_type="model",
private=PRIVATE_REPO,
exist_ok=True,
)
print(f"目标仓库：{repo_url}")
print("开始上传文件……")
# 上传文件夹内的全部内容
# path_in_repo="" 表示上传到仓库根目录
commit_info = api.upload_folder(
folder_path=str(LOCAL_FOLDER),
repo_id=REPO_ID,
repo_type="model",
path_in_repo="",
commit_message=COMMIT_MESSAGE,
# 忽略常见的本地缓存和系统文件
ignore_patterns=[
".git/**",
".DS_Store",
"**/.DS_Store",
"__pycache__/**",
"**/__pycache__/**",
"*.pyc",
"**/*.pyc",
],
)
print("\n上传完成。")
print(f"模型仓库：https://huggingface.co/{REPO_ID}")
commit_url = getattr(commit_info, "commit_url", None)
if commit_url:
print(f"本次提交：{commit_url}")
except HfHubHTTPError as exc:
print("\nHugging Face 请求失败：", file=sys.stderr)
print(str(exc), file=sys.stderr)
if exc.response is not None:
if exc.response.status_code == 401:
print(
"\n可能原因：Token 无效、已过期或没有登录权限。",
file=sys.stderr,
)
elif exc.response.status_code == 403:
print(
"\n可能原因：Token 没有写入权限，"
"或者当前账户无权写入 bingjie/DiffAM。",
file=sys.stderr,
)
raise
except KeyboardInterrupt:
print("\n上传已由用户中断。", file=sys.stderr)
sys.exit(130)
if __name__ == "__main__":
upload_folder() |