Mirrored_Repos/InvokeAI
1
0
Fork 0
mirror of https://github.com/invoke-ai/InvokeAI synced 2024-08-30 20:32:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

(config) try to authenticate to Huggingface more eagerly, using env vars

Browse Source
This commit is contained in:
Eugene Brodsky 2022-11-27 05:23:42 -05:00 committed by Lincoln Stein
parent f237744ab1
commit ed6194351c
1 changed files with 11 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

15
scripts/configure_invokeai.py
View File

@ -212,8 +212,7 @@ This involves a few easy steps.
access_token = HfFolder.get_token()
if access_token is not None:
print('found')
if access_token is None:
else:
print('not found')
print('''
4. Thank you! The last step is to enter your HuggingFace access token so that
@ -231,6 +230,7 @@ This involves a few easy steps.
Token: '''
)
access_token = getpass_asterisk.getpass_asterisk()
HfFolder.save_token(access_token)
return access_token
#---------------------------------------------
@ -521,10 +521,16 @@ def download_safety_checker():
print('...success',file=sys.stderr)
#-------------------------------------
def download_weights(opt:dict):
# Authenticate to Huggingface using environment variables.
# If successful, authentication will persist for either interactive or non-interactive use.
# Default env var expected by HuggingFace is HUGGING_FACE_HUB_TOKEN.
if not (access_token := HfFolder.get_token()):
# If unable to find an existing token or expected environment, try the non-canonical environment variable (widely used in the community and supported as per docs)
if (access_token := os.getenv("HUGGINGFACE_TOKEN")):
HfFolder.save_token(access_token)
if opt.yes_to_all:
models = recommended_datasets()
access_token = HfFolder.get_token()
if len(models)>0 and access_token is not None:
successfully_downloaded = download_weight_datasets(models, access_token)
update_config_file(successfully_downloaded,opt)
@ -547,6 +553,7 @@ def download_weights(opt:dict):
return
print('** LICENSE AGREEMENT FOR WEIGHT FILES **')
# We are either already authenticated, or will be asked to provide the token interactively
access_token = authenticate()
print('\n** DOWNLOADING WEIGHTS **')
successfully_downloaded = download_weight_datasets(models, access_token)