Upload 2 files

app.py

@@ -9,7 +9,7 @@ import copy
 import random
 import time
 from mod import (models, clear_cache, get_repo_safetensors, change_base_model,
-                 description_ui, num_loras, compose_lora_json, is_valid_lora, fuse_loras, get_trigger_word)
+                 description_ui, num_loras, compose_lora_json, is_valid_lora, fuse_loras, get_trigger_word, pipe)
 from flux import (search_civitai_lora, select_civitai_lora, search_civitai_lora_json,
                   download_my_lora, get_all_lora_tupled_list, apply_lora_prompt,
                   update_loras)
@@ -22,10 +22,6 @@ from tagger.fl2flux import predict_tags_fl2_flux
 with open('loras.json', 'r') as f:
     loras = json.load(f)
 
-# Initialize the base model
-base_model = models[0]
-pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
-
 MAX_SEED = 2**32-1
 
 class calculateDuration:
@@ -228,7 +224,7 @@ with gr.Blocks(theme=gr.themes.Soft(), fill_width=True, css=css) as app:
         outputs=[result, seed]
     )
 
-    model_name.change(change_base_model, [model_name], None)
+    model_name.change(change_base_model, [model_name], None, queue=False)
 
     gr.on(
         triggers=[lora_search_civitai_submit.click, lora_search_civitai_query.submit],

mod.py

@@ -68,12 +68,15 @@ def get_repo_safetensors(repo_id: str):
     else: return gr.update(value=files[0], choices=files)
 
 
+# Initialize the base model
+base_model = models[0]
+pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
+
+
 def change_base_model(repo_id: str):
-    from huggingface_hub import HfApi
     global pipe
-    api = HfApi()
     try:
-        if " " in repo_id or not api.repo_exists(repo_id): return
+        if not is_repo_name(repo_id) or not is_repo_exists(repo_id): return
         clear_cache()
         pipe = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=torch.bfloat16)
     except Exception as e: