README.md

metadata

license: apache-2.0
language:
  - ch

此huggingface库主要存储本人电脑的一些重要文件

如果无法下载文件，把下载链接的huggingface.co改成hf-mirror.com 即可

如果你也想要在此处永久备份文件，可以参考我的上传代码：

# 功能函数，清理打包上传
from pathlib import Path
from huggingface_hub import HfApi, login

repo_id = 'ACCC1380/private-model'
yun_folders = ['/kaggle/input']


def hugface_upload(yun_folders, repo_id):
    if 5 == 5:
        hugToken = '********************' #改成你的huggingface_token
        if hugToken != '':
            login(token=hugToken)
            api = HfApi()
            print("HfApi 类已实例化")
            print("开始上传文件...")
            for yun_folder in yun_folders:
                folder_path = Path(yun_folder)
                if folder_path.exists() and folder_path.is_dir():
                    for file_in_folder in folder_path.glob('**/*'):
                        if file_in_folder.is_file():
                            try:
                                response = api.upload_file(
                                    path_or_fileobj=file_in_folder,
                                    path_in_repo=str(file_in_folder.relative_to(folder_path.parent)),
                                    repo_id=repo_id,
                                    repo_type="dataset"
                                )
                                print("文件上传完成")
                                print(f"响应: {response}")
                            except Exception as e:
                                print(f"文件 {file_in_folder} 上传失败: {e}")
                                continue
                else:
                    print(f'Error: Folder {yun_folder} does not exist')
        else:
            print(f'Error: File {huggingface_token_file} does not exist')

hugface_upload(yun_folders, repo_id)

本地电脑需要梯子环境，上传可能很慢。可以使用kaggle等中转服务器上传，下载速率400MB/s，上传速率60MB/s。

在kaggle上面转存模型：

• 第一步：下载文件

!apt install -y aria2
!aria2c -x 16 -s 16 -c -k 1M "https://huggingface.co./AstraliteHeart/pony-diffusion-v6/resolve/main/v6.safetensors"

• 第二步：使用上述代码的API上传

# 功能函数，清理打包上传
from pathlib import Path
from huggingface_hub import HfApi, login

repo_id = 'ACCC1380/private-model'
yun_folders = ['/kaggle/working'] #kaggle的output路径


def hugface_upload(yun_folders, repo_id):
    if 5 == 5:
        hugToken = '********************' #改成你的huggingface_token
        if hugToken != '':
            login(token=hugToken)
            api = HfApi()
            print("HfApi 类已实例化")
            print("开始上传文件...")
            for yun_folder in yun_folders:
                folder_path = Path(yun_folder)
                if folder_path.exists() and folder_path.is_dir():
                    for file_in_folder in folder_path.glob('**/*'):
                        if file_in_folder.is_file():
                            try:
                                response = api.upload_file(
                                    path_or_fileobj=file_in_folder,
                                    path_in_repo=str(file_in_folder.relative_to(folder_path.parent)),
                                    repo_id=repo_id,
                                    repo_type="dataset"
                                )
                                print("文件上传完成")
                                print(f"响应: {response}")
                            except Exception as e:
                                print(f"文件 {file_in_folder} 上传失败: {e}")
                                continue
                else:
                    print(f'Error: Folder {yun_folder} does not exist')
        else:
            print(f'Error: File {huggingface_token_file} does not exist')

hugface_upload(yun_folders, repo_id)

• 第三步：等待上传完成：