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---
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：
```python
# 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
```notebook
!apt install -y aria2
!aria2c -x 16 -s 16 -c -k 1M "把下载链接填到这双引号里" -o "保存的文件名称.safetensors"
```
- 第二步：使用上述代码的API上传
```python
# 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：
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