Update app.py

app.py

@@ -23,7 +23,6 @@ pipe = StableDiffusionXLPipeline.from_single_file(
     variant = "fp16",
     vae = vae,
     use_safetensors = True,
-    scheduler_type = "ddim",
     use_auth_token="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"
 )
 pipe.enable_model_cpu_offload()
@@ -32,6 +31,7 @@ pipeRefiner = StableDiffusionXLImg2ImgPipeline.from_pretrained(
     "stabilityai/stable-diffusion-xl-refiner-1.0",
     torch_dtype=torch.float16,
     variant="fp16",
+    vae=vae,
     use_safetensors=True
 )
 pipeRefiner.enable_model_cpu_offload()
@@ -57,16 +57,17 @@ def generate(prompt, neg_prompt, samp_steps, guide_scale, batch_size, seed, heig
         guidance_scale=guide_scale,
         #cross_attention_kwargs={"scale": lora_scale},
         num_images_per_prompt=batch_size,
-        height=height/2,
-        width=width/2,
+        height=height,
+        width=width,
         generator=torch.manual_seed(seed),
+        output_type="latent",
+        denoising_end=0.8
     ).images
-    imagesRefined = pipeRefiner(
+    images = pipeRefiner(
         prompt,
         image=images,
-        num_inference_steps=5,
-        height=height,
-        width=width
+        num_inference_steps=samp_steps,
+        denoising_start=0.8
     ).images
     return [(img, f"Image {i+1}") for i, img in enumerate(imagesRefined)]