Upload genimage.py

genimage.py

@@ -6,7 +6,7 @@ def load_pipeline():
     import torch
     device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
     pipe = DiffusionPipeline.from_pretrained(
-        "John6666/rae-diffusion-xl-v2-sdxl-spo-dpo-turbo",
+        "John6666/rae-diffusion-xl-v2-sdxl-spo-pcm",
         custom_pipeline="lpw_stable_diffusion_xl",
         torch_dtype=torch.float16,
     )
@@ -38,9 +38,9 @@ def generate_image(prompt, neg_prompt):
         "prompt": prompt,
         "negative_prompt": neg_prompt,
         "resolution": f"{1024} x {1024}",
-        "guidance_scale": 2,
+        "guidance_scale": 7.5,
         "num_inference_steps": 16,
-        "sampler": "LCM",
+        "sampler": "Euler",
     }
     try: 
         images = pipe(
@@ -50,7 +50,7 @@ def generate_image(prompt, neg_prompt):
             negative_prompt_2="lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract], photo, deformed, disfigured, low contrast, photo, deformed, disfigured, low contrast",
             width=1024,
             height=1024,
-            guidance_scale=2,
+            guidance_scale=7.5,
             num_inference_steps=16,
             output_type="pil",
             clip_skip=1,