fix handling of online model configs

CHANGELOG.md

@@ -38,6 +38,7 @@ Other improvements:
   improves quality of the flow-matching samplers  
 - t5 support manually downloaded models  
   applies to all models that use t5 transformer  
+- fix handling of model configs if offline config is not available  
 
 Work-in-progress:
 - flux controlnet support: (*1)

modules/sd_models.py

@@ -1213,10 +1213,10 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
                 if model_type.startswith('Stable Diffusion'):
                     if shared.opts.diffusers_force_zeros:
                         diffusers_load_config['force_zeros_for_empty_prompt '] = shared.opts.diffusers_force_zeros
-                    if diffusers_version < 28:
-                        diffusers_load_config['original_config_file'] = get_load_config(checkpoint_info.path, model_type, config_type='yaml')
                     else:
-                        diffusers_load_config['config'] = get_load_config(checkpoint_info.path, model_type, config_type='json')
+                        model_config = get_load_config(checkpoint_info.path, model_type, config_type='json')
+                        if model_config is not None:
+                            diffusers_load_config['config_files'] = model_config
                 if model_type.startswith('Stable Diffusion 3'):
                     from modules.model_sd3 import load_sd3
                     sd_model = load_sd3(fn=checkpoint_info.path, cache_dir=shared.opts.diffusers_dir, config=diffusers_load_config.get('config', None))

modules/sd_vae.py

@@ -212,9 +212,11 @@ def load_vae_diffusers(model_file, vae_file=None, vae_source="unknown-source"):
         import diffusers
         if os.path.isfile(vae_file):
             _pipeline, model_type = sd_models.detect_pipeline(model_file, 'vae')
-            diffusers_load_config = {
-                "config": os.path.join(sd_models.get_load_config(model_file, model_type, config_type='json'), 'vae'),
-            }
+            vae_config = sd_models.get_load_config(model_file, model_type, config_type='json')
+            if vae_config is not None:
+                diffusers_load_config = {
+                    "config": os.path.join(vae_config, 'vae'),
+                }
             if os.path.getsize(vae_file) > 1310944880: # 1.3GB
                 vae = diffusers.ConsistencyDecoderVAE.from_pretrained('openai/consistency-decoder', **diffusers_load_config) # consistency decoder does not have from single file, so we'll just download it once more
             elif os.path.getsize(vae_file) < 10000000: # 10MB