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from blacklist import bad_tags,bad_models,fav_models
models = []
models_plus_tags=[]
tags_plus_models=[]
def list_uniq(l):
return sorted(set(l), key=l.index)
def find_model_list(author: str="", tags: list[str]=[], not_tag="", sort: str="last_modified", limit: int=30, force_gpu=False, check_status=False, bad_models=bad_models):
from huggingface_hub import HfApi
api = HfApi()
default_tags = ["diffusers"]
if not sort: sort = "last_modified"
models = []
models_plus_tags=[]
try:
model_infos = api.list_models(author=author, task="text-to-image",
tags=list_uniq(default_tags + tags), cardData=True, sort=sort, limit=limit)
except Exception as e:
print(f"Error: Failed to list models.")
print(e)
return models
for model in model_infos:
if not model.private and not model.gated:
loadable = True
if not_tag and not_tag in model.tags or not loadable: continue
if model.id not in bad_models :
models.append(model.id)
#models_plus_tags.append([model.id,process_tags(model.tags)])
models_plus_tags.append([model.id,process_tags(model.cardData.tags)])
if len(models) == limit: break
return models , models_plus_tags
def process_tags(tags,bad_tags=bad_tags):
t1=True
new_tags=[]
for tag in tags:
if tag not in bad_tags:
if tag == 'en':
t1=False
if t1 :
new_tags.append(tag)
return new_tags
def clas_tags(models_plus_tags,min):
tags_plus_models=[]
listTemp=[]
listAllModels=['all',0,[]]
new_tag=True
for ent in models_plus_tags:
listAllModels[1]+=1
listAllModels[2].append(ent[0])
for tagClas in ent[1]:
new_tag=True
for tag in listTemp:
if tag[0] == tagClas:
tag[1]+=1
tag[2].append(ent[0])
new_tag=False
if new_tag:
listTemp.append([tagClas,1,[ent[0]]])
tags_plus_models.append(listAllModels)
for t in listTemp:
if t[1]>=min and t[1]!=len(models_plus_tags):
tags_plus_models.append(t)
return tags_plus_models
def orga_tag(tags_plus_models):
output=[]
while(len(output)<len(tags_plus_models)):
max=0
for tag in tags_plus_models:
if tag[1]>max:
if tag not in output:
max=tag[1]
tagMax=tag
output.append(tagMax)
return output
def tag_new(models,limit=40):
output=["NEW",0,[]]
if limit>len(models):
limit=len(models)
for i in range(limit):
output[1]+=1
output[2].append(models[i])
return output
def tag_fav(models=models,fav_models=fav_models):
output=["FAV",0,[]]
for m in fav_models:
if m in models:
output[1]+=1
output[2].append(m)
return output
def update_tag(models_plus_tags,list_new_tag):
for m_new in list_new_tag[2]:
for m in models_plus_tags:
if m_new == m[0]:
m[1].append(list_new_tag[0])
return models_plus_tags
from operator import itemgetter
#models = find_model_list("Yntec", [], "", "last_modified", 20)
models , models_plus_tags = find_model_list("John6666", ["stable-diffusion-xl"], "", "last_modified", 2000)
#tags_plus_models = orga_tag(clas_tags(models_plus_tags,2))
tags_plus_models = orga_tag(clas_tags(sorted(models_plus_tags, key=itemgetter(0)),2))
list_new=tag_new(models,40)
models_plus_tags=update_tag(models_plus_tags,list_new)
tags_plus_models.insert(1,list_new)
list_fav=tag_fav()
if list_fav[1]>0:
tags_plus_models.insert(1,list_fav)
models_plus_tags=update_tag(models_plus_tags,list_fav)
#models.extend(find_model_list("John6666", ["stable-diffusion-xl"], "", "last_modified", 200))
#models.extend(find_model_list("John6666", [], "", "last_modified", 20)) # The latest 20 models will be added to the models written above.
# Examples:
#models = ['yodayo-ai/kivotos-xl-2.0', 'yodayo-ai/holodayo-xl-2.1'] # specific models
#models = find_model_list("Yntec", [], "", "last_modified", 20) # Yntec's latest 20 models
#models = find_model_list("Yntec", ["anime"], "", "last_modified", 20) # Yntec's latest 20 models with 'anime' tag
#models = find_model_list("Yntec", [], "anime", "last_modified", 20) # Yntec's latest 20 models without 'anime' tag
#models = find_model_list("", [], "", "last_modified", 20) # latest 20 text-to-image models of huggingface
#models = find_model_list("", [], "", "downloads", 20) # monthly most downloaded 20 text-to-image models of huggingface
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