updated v3p3

app.py

@@ -15,6 +15,58 @@ from diffusers import StableDiffusionXLPipeline, StableDiffusionXLImg2ImgPipelin
 
 # ... (keep the existing imports and configurations)
 
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+DESCRIPTION = "PonyDiffusion V6 XL"
+if not torch.cuda.is_available():
+    DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU. </p>"
+IS_COLAB = utils.is_google_colab() or os.getenv("IS_COLAB") == "1"
+HF_TOKEN = os.getenv("HF_TOKEN")
+CACHE_EXAMPLES = torch.cuda.is_available() and os.getenv("CACHE_EXAMPLES") == "1"
+MIN_IMAGE_SIZE = int(os.getenv("MIN_IMAGE_SIZE", "512"))
+MAX_IMAGE_SIZE = int(os.getenv("MAX_IMAGE_SIZE", "2048"))
+USE_TORCH_COMPILE = os.getenv("USE_TORCH_COMPILE") == "1"
+ENABLE_CPU_OFFLOAD = os.getenv("ENABLE_CPU_OFFLOAD") == "1"
+OUTPUT_DIR = os.getenv("OUTPUT_DIR", "./outputs")
+
+MODEL = os.getenv(
+    "MODEL",
+    "https://huggingface.co/AstraliteHeart/pony-diffusion-v6/blob/main/v6.safetensors",
+)
+
+torch.backends.cudnn.deterministic = True
+torch.backends.cudnn.benchmark = False
+
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+
+
+def load_pipeline(model_name):
+    vae = AutoencoderKL.from_pretrained(
+        "madebyollin/sdxl-vae-fp16-fix",
+        torch_dtype=torch.float16,
+    )
+    pipeline = (
+        StableDiffusionXLPipeline.from_single_file
+        if MODEL.endswith(".safetensors")
+        else StableDiffusionXLPipeline.from_pretrained
+    )
+
+    pipe = pipeline(
+        model_name,
+        vae=vae,
+        torch_dtype=torch.float16,
+        custom_pipeline="lpw_stable_diffusion_xl",
+        use_safetensors=True,
+        add_watermarker=False,
+        use_auth_token=HF_TOKEN,
+        variant="fp16",
+    )
+
+    pipe.to(device)
+    return pipe
+
+
 # Add a new function to parse and validate JSON input
 def parse_json_parameters(json_str):
     try: