Update app.py

app.py

@@ -4,6 +4,7 @@ import random
 from optimum.intel import OVStableDiffusionXLPipeline
 import torch
 from diffusers import EulerDiscreteScheduler
+from diffusers import LCMScheduler
 
 model_id = "None1145/noobai-XL-Vpred-0.65s-openvino"
 
@@ -19,9 +20,12 @@ def reload_model(new_model_id):
     try:
         print(f"{model_id}...")
         pipe = OVStableDiffusionXLPipeline.from_pretrained(model_id, compile=False)
-        if model_id == "None1145/noobai-XL-Vpred-0.65s-openvino" or "Vpred" in model_id or "vpred" in model_id or "v-pred" in model_id:
+        if model_id == "None1145/noobai-XL-Vpred-0.65s-openvino":
             scheduler_args = {"prediction_type": "v_prediction", "rescale_betas_zero_snr": True}
-            pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, **scheduler_args)
+            # pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config, **scheduler_args)
+            pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config, **scheduler_args)
+            pipe.load_lora_weights("latent-consistency/lcm-lora-sdxl")
+            pipe.fuse_lora()
         # pipe.to("gpu")
         pipe.reshape(batch_size=1, height=prev_height, width=prev_width, num_images_per_prompt=1)
         pipe.compile()
@@ -82,6 +86,14 @@ with gr.Blocks() as img:
                 container=False,
             )
 
+            num_inference_steps = gr.Slider(
+                label="Number of inference steps",
+                minimum=1,
+                maximum=60,
+                step=1,
+                value=5,
+            )
+
             run_button = gr.Button("Run", scale=0, variant="primary")
 
         result = gr.Image(label="Result", show_label=False)
@@ -130,14 +142,6 @@ with gr.Blocks() as img:
                     value=5.0,
                 )
 
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=60,
-                    step=1,
-                    value=28,
-                )
-
         gr.Examples(examples=examples, inputs=[prompt])
     
     gr.Markdown("### Model Reload")