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Duplicate from lora-library/LoRA-DreamBooth-Training-UI
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from __future__ import annotations
from huggingface_hub import HfApi
class Uploader:
def __init__(self, hf_token: str | None):
self.api = HfApi(token=hf_token)
def get_username(self) -> str:
return self.api.whoami()['name']
def upload(self,
folder_path: str,
repo_name: str,
organization: str = '',
repo_type: str = 'model',
private: bool = True,
delete_existing_repo: bool = False) -> str:
if not folder_path:
raise ValueError
if not repo_name:
raise ValueError
if not organization:
organization = self.get_username()
repo_id = f'{organization}/{repo_name}'
if delete_existing_repo:
try:
self.api.delete_repo(repo_id, repo_type=repo_type)
except Exception:
pass
try:
self.api.create_repo(repo_id, repo_type=repo_type, private=private)
self.api.upload_folder(repo_id=repo_id,
folder_path=folder_path,
path_in_repo='.',
repo_type=repo_type)
url = f'https://huggingface.co/{repo_id}'
message = f'Your model was successfully uploaded to <a href="{url}" target="_blank">{url}</a>.'
except Exception as e:
message = str(e)
return message