updated scheduler for turbo model

.gradio/certificate.pem

@@ -0,0 +1,31 @@
+-----BEGIN CERTIFICATE-----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=
+-----END CERTIFICATE-----

src/sdgen/sd/pipeline.py

@@ -8,7 +8,7 @@ from typing import Optional
 import torch
 from diffusers import (
     DPMSolverMultistepScheduler,
-    EulerAncestralDiscreteScheduler,
+    LCMScheduler,
     StableDiffusionPipeline,
 )
 
@@ -54,7 +54,7 @@ def load_pipeline(
     if scheduler is None:
         try:
             if "turbo" in model_id.lower():
-                scheduler = EulerAncestralDiscreteScheduler.from_pretrained(
+                scheduler = LCMScheduler.from_pretrained(
                     model_id,
                     subfolder="scheduler",
                 )
@@ -127,7 +127,7 @@ def warmup_pipeline(
         pipe(
             prompt=prompt,
             num_inference_steps=1,
-            guidance_scale=1.0,
+            guidance_scale=0.0,
             height=height,
             width=width,
             generator=generator,

src/sdgen/ui/layout.py

@@ -40,11 +40,11 @@ def _resolve_seed(value: Any) -> int | None:
         return None
 
 
-def _update_steps(model):
+def _update_steps_and_cfg(model):
     """Upate steps based on the model."""
     if model == "Turbo":
-        return gr.update(minimum=1, maximum=10, value=6, step=1)
-    return gr.update(minimum=10, maximum=30, value=20, step=1)
+        return (gr.update(minimum=1, maximum=5, value=2, step=1), gr.update(minimum=0, maximum=0, value=0, step=0))
+    return (gr.update(minimum=10, maximum=30, value=20, step=1), 7.5)
 
 
 def _txt2img_handler(
@@ -195,8 +195,7 @@ def build_ui(txt2img_pipes: dict, img2img_pipes: dict) -> gr.Blocks:
     with gr.Blocks() as demo:
         gr.Markdown(
             "# Stable Diffusion Generator\n"
-            "Clean, local Stable \
-            Diffusion toolkit."
+            "Generation can take from few seconds to several minutes based on the Model selceted and applied settings."
         )
 
         model_choice = gr.Dropdown(
@@ -207,6 +206,7 @@ def build_ui(txt2img_pipes: dict, img2img_pipes: dict) -> gr.Blocks:
             value="SD1.5",
             label="Model",
         )
+        gr.Markdown("Use Turbo model if you prefer speed over quality.")
 
         txt_controls = build_txt2img_tab(
             make_txt2img_handler(model_choice.value, txt2img_pipes),
@@ -228,14 +228,14 @@ def build_ui(txt2img_pipes: dict, img2img_pipes: dict) -> gr.Blocks:
         build_history_tab()
 
         model_choice.change(
-            fn=_update_steps,
+            fn=_update_steps_and_cfg,
             inputs=[model_choice],
-            outputs=[txt_controls.steps],
+            outputs=[txt_controls.steps, txt_controls.guidance],
         )
         model_choice.change(
-            fn=_update_steps,
+            fn=_update_steps_and_cfg,
             inputs=[model_choice],
-            outputs=[img_controls.steps],
+            outputs=[img_controls.steps, img_controls.guidance],
         )
 
         gr.Markdown(
@@ -243,9 +243,7 @@ def build_ui(txt2img_pipes: dict, img2img_pipes: dict) -> gr.Blocks:
             "- Use **History → Refresh** if new entries do not appear.\n"
             "- Presets apply to both **Text → Image** and \
  **Image → Image** tabs.\n"
-            "- Inference speed will be much faster on GPU \
-(This app is hosted on CPU based HF Spaces).\n"
-            "- Use Turbo model if you prefer speed over performance."
+            "- This app is hosted on CPU based HF Spaces, so generation may take some time, please be patient.\n"
         )
 
     return demo

src/sdgen/ui/tabs/img2img_tab.py

@@ -52,7 +52,7 @@ def build_img2img_tab(handler: Callable[..., Tuple[Any, dict]]) -> Img2ImgContro
                 strength = gr.Slider(
                     minimum=0.1,
                     maximum=1.0,
-                    value=0.6,
+                    value=0.5,
                     step=0.05,
                     label="Strength",
                 )
@@ -88,7 +88,7 @@ the prompt more strictly. "
                     value="",
                     placeholder="Leave empty for random",
                 )
-
+                gr.Markdown("If using Turbo model, ensure steps*strength >=1")
                 generate_button = gr.Button("Generate")
 
             with gr.Column():