Update app.py

app.py

@@ -6,7 +6,7 @@ import numpy as np
 import spaces
 import random
 import string
-from diffusers import StableDiffusion3Pipeline
+from diffusers import AutoPipelineForText2Image
 import torch
 from pathos.multiprocessing import ProcessingPool as ProcessPoolExecutor
 import requests
@@ -16,15 +16,16 @@ pool = ProcessPoolExecutor(4)
 pool.__enter__()
 
 #model_id = "runwayml/stable-diffusion-v1-5"
-model_id = "stabilityai/stable-diffusion-3-medium-diffusers"
+#model_id = "stabilityai/stable-diffusion-3-medium-diffusers"
+model_id = "kandinsky-community/kandinsky-2-2-decoder"
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 if torch.cuda.is_available():
     torch.cuda.max_memory_allocated(device=device)
-    pipe = StableDiffusion3Pipeline.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16", use_safetensors=True, token=os.getenv('hf_token'))
+    pipe = AutoPipelineForText2Image.from_pretrained(model_id, torch_dtype=torch.float16, variant="fp16", use_safetensors=True, token=os.getenv('hf_token'))
     pipe = pipe.to(device)
 else: 
-    pipe = StableDiffusion3Pipeline.from_pretrained(model_id, use_safetensors=True, token=os.getenv('hf_token'))
+    pipe = AutoPipelineForText2Image.from_pretrained(model_id, use_safetensors=True, token=os.getenv('hf_token'))
     pipe = pipe.to(device)
 
 def translate(text,lang):
@@ -74,16 +75,16 @@ def generate_random_string(length):
 def Piper(_do):
     return pipe(
         _do,
-        height=448,
-        width=448,
-        negative_prompt='vivid colors; text; logo',
-        num_inference_steps=125,
-        guidance_scale=9
+        height=768,
+        width=512,
+        negative_prompt='ugly, deformed, disfigured, poor details, bad anatomy, labels, texts, logos',
+        num_inference_steps=50,
+        guidance_scale=8.5
     )
 
 def infer(prompt):
     name = generate_random_string(12)+".png"
-    _do = f'acrylic colors; { translate(prompt,"english") }; photograph-like real'.upper()
+    _do = f'{ translate(prompt,"english") }, cold color palette, muted colors, detailed, 8k'.lower()
     image = Piper(_do).images[0].save(name)
     return name