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Added custom text box for loading models from specific path, or loading other models from hugging face.

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This commit is contained in:
ebolam
2022-06-13 13:48:45 -04:00
parent 5110e956d2
commit 11ed55f34a
3 changed files with 25 additions and 7 deletions
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28
aiserver.py
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@ -434,13 +434,15 @@ def getModelSelection(modellist):
getModelSelection(mainmenu)
def check_if_dir_is_model(path):
try:
from transformers import AutoConfig
model_config = AutoConfig.from_pretrained(path, revision=vars.revision, cache_dir="cache")
except:
if os.path.exists(path):
try:
from transformers import AutoConfig
model_config = AutoConfig.from_pretrained(path, revision=vars.revision, cache_dir="cache")
except:
return False
return True
else:
return False
return True
#==================================================================#
# Return all keys in tokenizer dictionary containing char
@ -3056,12 +3058,24 @@ def get_message(msg):
# The data variable will contain the model name. But our Custom lines need a bit more processing
# If we're on a custom line that we have selected a model for, the path variable will be in msg
# so if that's missing we need to run the menu to show the model folders in the models folder
if msg['data'] in ('NeoCustom', 'GPT2Custom') and 'path' not in msg:
if msg['data'] in ('NeoCustom', 'GPT2Custom') and 'path' not in msg and 'path_modelname' not in msg:
if 'folder' not in msg:
folder = "./models"
else:
folder = msg['folder']
sendModelSelection(menu=msg['data'], folder=folder)
elif msg['data'] in ('NeoCustom', 'GPT2Custom') and 'path_modelname' in msg:
#Here the user entered custom text in the text box. This could be either a model name or a path.
if check_if_dir_is_model(msg['path_modelname']):
vars.model = msg['data']
vars.custmodpth = msg['path_modelname']
get_model_info(msg['data'], directory=msg['path'])
else:
vars.model = msg['path_modelname']
try:
get_model_info(vars.model)
except:
emit('from_server', {'cmd': 'errmsg', 'data': "The model entered doesn't exist."})
elif msg['data'] in ('NeoCustom', 'GPT2Custom'):
if check_if_dir_is_model(msg['path']):
vars.model = msg['data']