Update app.py

app.py

@@ -74,6 +74,14 @@ pipe.load_lora_weights(
     adapter_name="lora_h", **kwargs_lora_h
 )
 
+kwargs_lora_gh = {}
+kwargs_lora_gh["load_into_transformer"] = True
+pipe.load_lora_weights(
+    "GiorgioV/LoRA_for_WAN_22", 
+    weight_name="Wan2.2 - I2V - GH - HIGH 14B.safetensors", 
+    adapter_name="lora_gh", **kwargs_lora_gh
+)
+
 kwargs_lora = {}
 kwargs_lora["load_into_transformer_2"] = True
 pipe.load_lora_weights(
@@ -90,24 +98,35 @@ pipe.load_lora_weights(
     adapter_name="lora_l", **kwargs_lora_l
 )
 
+kwargs_lora_gl = {}
+kwargs_lora_gl["load_into_transformer_2"] = True
+pipe.load_lora_weights(
+    "GiorgioV/LoRA_for_WAN_22", 
+    weight_name="Wan2.2 - I2V - GH - LOW 14B.safetensors", 
+    adapter_name="lora_gl", **kwargs_lora_gl
+)
+
 kwargs_lora_djl = {}
 kwargs_lora_djl["load_into_transformer_2"] = True
 pipe.load_lora_weights(
     "GiorgioV/LoRA_for_WAN_22", 
     weight_name="DJ_I2V_14b_LowNoise.safetensors", 
-    adapter_name="lora_djl", **kwargs_lora_djl
+    adapter_name="lora_gjl", **kwargs_lora_djl
 )
 
 
 
-pipe.set_adapters(["lightx2v", "lora_h", "lightx2v_2", "lora_l", "lora_djl"], adapter_weights=[1., 1., 1., 1., 1.])
+pipe.set_adapters(["lightx2v", "lora_h", "lora_gh", "lightx2v_2", "lora_l", "lora_gl", "lora_gjl"], adapter_weights=[1., 1., 1., 1., 1., 1., 1.])
 pipe.fuse_lora(adapter_names=["lightx2v"], lora_scale=3., components=["transformer"])
 pipe.fuse_lora(adapter_names=["lora_h"], lora_scale=0.3, components=["transformer"])
+pipe.fuse_lora(adapter_names=["lora_gh"], lora_scale=0.3, components=["transformer"])
 pipe.fuse_lora(adapter_names=["lightx2v_2"], lora_scale=1., components=["transformer_2"])
-pipe.fuse_lora(adapter_names=["lora_l"], lora_scale=0.8, components=["transformer_2"])
-pipe.fuse_lora(adapter_names=["lora_djl"], lora_scale=0.8, components=["transformer_2"])
+pipe.fuse_lora(adapter_names=["lora_l"], lora_scale=1., components=["transformer_2"])
+pipe.fuse_lora(adapter_names=["lora_gl"], lora_scale=0.8, components=["transformer_2"])
+pipe.fuse_lora(adapter_names=["lora_gjl"], lora_scale=0.8, components=["transformer_2"])
 pipe.unload_lora_weights()
 
+
 quantize_(pipe.text_encoder, Int8WeightOnlyConfig())
 quantize_(pipe.transformer, Float8DynamicActivationFloat8WeightConfig())
 quantize_(pipe.transformer_2, Float8DynamicActivationFloat8WeightConfig())