lora exp 2 with config

app.py

@@ -9,6 +9,7 @@ from diffusers.schedulers.scheduling_unipc_multistep import UniPCMultistepSchedu
 from diffusers.schedulers.scheduling_flow_match_euler_discrete import FlowMatchEulerDiscreteScheduler
 from huggingface_hub import hf_hub_download
 from lycoris import create_lycoris_from_weights
+from transformers import AutoConfig
 
 # Define model options
 MODEL_OPTIONS = {
@@ -69,9 +70,12 @@ def generate_video(
         seed = int(seed)
     
     torch.manual_seed(seed)
+
+    # Load config from the model
+    config = AutoConfig.from_pretrained(model_id)
     
-    vae = AutoencoderKLWan.from_pretrained(model_id, subfolder="vae", torch_dtype=torch.float32)
-    pipe = WanPipeline.from_pretrained(model_id, vae=vae, torch_dtype=torch.float16)
+    vae = AutoencoderKLWan.from_pretrained(model_id, subfolder="vae", config=config, torch_dtype=torch.float32)
+    pipe = WanPipeline.from_pretrained(model_id, vae=vae, config=config, torch_dtype=torch.float16)
     
     if scheduler_type == "UniPCMultistepScheduler":
         pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=flow_shift)
@@ -222,30 +226,26 @@ with gr.Blocks() as demo:
             
     generate_btn.click(
         fn=generate_video,
-        inputs=[model_choice,
-                prompt,
-                negative_prompt,
-                lycoris_id,
-                lycoris_weight_name,
-                lycoris_scale,
-                scheduler_type,
-                flow_shift,
-                height,
-                width,
-                num_frames,
-                guidance_scale,
-                num_inference_steps,
-                output_fps,
-                seed],
+        inputs=[ 
+            model_choice,
+            prompt,
+            negative_prompt,
+            lycoris_id,
+            lycoris_weight_name,
+            lycoris_scale,
+            scheduler_type,
+            flow_shift,
+            height,
+            width,
+            num_frames,
+            guidance_scale,
+            num_inference_steps,
+            output_fps,
+            seed
+        ],
         outputs=[output_video, used_seed]
     )
     
-    gr.Markdown("""
-    ## Tips for best results:
-    - Smaller videos: Flow shift 2.0–5.0
-    - Larger videos: Flow shift 7.0–12.0
-    - Use frame count in 4k+1 form (e.g., 33, 65)
-    - Limit frame count and resolution to avoid timeout
-    """)
+    gr.Markdown(""" ## Tips for best results: - Smaller videos: Flow shift 2.0–5.0 - Larger videos: Flow shift 7.0–12.0 - Use frame count in 4k+1 form (e.g., 33, 65) - Limit frame count and resolution to avoid timeout """)
 
 demo.launch()