Update app.py (#3)

- Update app.py (387b44947c08b15b27376a91f61589aad6d6f9c4)
- Update optimization.py (8500e75eee1612f87a9dc893a17af0b4bb56ea32)

app.py

@@ -32,16 +32,16 @@ MAX_DURATION = round(MAX_FRAMES_MODEL/FIXED_FPS,1)
 
 vae = AutoencoderKLWan.from_pretrained("Wan-AI/Wan2.2-T2V-A14B-Diffusers", subfolder="vae", torch_dtype=torch.float32)
 pipe = WanPipeline.from_pretrained(MODEL_ID,
-    # transformer=WanTransformer3DModel.from_pretrained('cbensimon/Wan2.2-I2V-A14B-bf16-Diffusers',
-    #     subfolder='transformer',
-    #     torch_dtype=torch.bfloat16,
-    #     device_map='cuda',
-    # ),
-    # transformer_2=WanTransformer3DModel.from_pretrained('cbensimon/Wan2.2-I2V-A14B-bf16-Diffusers',
-    #     subfolder='transformer_2',
-    #     torch_dtype=torch.bfloat16,
-    #     device_map='cuda',
-    # ),
+    transformer=WanTransformer3DModel.from_pretrained('linoyts/Wan2.2-T2V-A14B-Diffusers-BF16',
+        subfolder='transformer',
+        torch_dtype=torch.bfloat16,
+        device_map='cuda',
+    ),
+    transformer_2=WanTransformer3DModel.from_pretrained('linoyts/Wan2.2-T2V-A14B-Diffusers-BF16',
+        subfolder='transformer_2',
+        torch_dtype=torch.bfloat16,
+        device_map='cuda',
+    ),
     vae=vae,
     torch_dtype=torch.bfloat16,
 ).to('cuda')

optimization.py

@@ -44,20 +44,20 @@ def optimize_pipeline_(pipeline: Callable[P, Any], *args: P.args, **kwargs: P.kw
     def compile_transformer():
         
         pipeline.load_lora_weights(
-           "vrgamedevgirl84/Wan14BT2VFusioniX", 
-           weight_name="FusionX_LoRa/Phantom_Wan_14B_FusionX_LoRA.safetensors", 
-            adapter_name="phantom"
+            "Kijai/WanVideo_comfy", 
+            weight_name="Lightx2v/lightx2v_I2V_14B_480p_cfg_step_distill_rank128_bf16.safetensors", 
+            adapter_name="lightx2v"
         )
         kwargs_lora = {}
         kwargs_lora["load_into_transformer_2"] = True
         pipeline.load_lora_weights(
-           "vrgamedevgirl84/Wan14BT2VFusioniX", 
-           weight_name="FusionX_LoRa/Phantom_Wan_14B_FusionX_LoRA.safetensors", 
-            adapter_name="phantom_2", **kwargs_lora
+            "Kijai/WanVideo_comfy", 
+            weight_name="Wan22-Lightning/Wan2.2-Lightning_T2V-A14B-4steps-lora_LOW_fp16.safetensors", 
+            adapter_name="lightx2v_2", **kwargs_lora
         )
-        pipeline.set_adapters(["phantom", "phantom_2"], adapter_weights=[1., 1.])
-        pipeline.fuse_lora(adapter_names=["phantom"], lora_scale=3., components=["transformer"])
-        pipeline.fuse_lora(adapter_names=["phantom_2"], lora_scale=1., components=["transformer_2"])
+        pipeline.set_adapters(["lightx2v", "lightx2v_2"], adapter_weights=[1., 1.])
+        pipeline.fuse_lora(adapter_names=["lightx2v"], lora_scale=3., components=["transformer"])
+        pipeline.fuse_lora(adapter_names=["lightx2v_2"], lora_scale=1., components=["transformer_2"])
         pipeline.unload_lora_weights()
         
         with capture_component_call(pipeline, 'transformer') as call: