Update app.py

app.py

@@ -1,36 +1,36 @@
 import torch
 import gradio as gr
-from diffusers import StableDiffusionXLPipeline, DPMSolverMultistepScheduler
-from peft import inject_adapter_in_model
+from diffusers import StableDiffusionXLPipeline
 from huggingface_hub import hf_hub_download
-import os
 
-# Download LoRA from HF Hub
-lora_path = hf_hub_download(repo_id="Leofreddare/DreamCartoonLora", filename="DreamCartoonLora.safetensors")
+# Download your LoRA weights
+lora_weights = hf_hub_download(
+    repo_id="Leofreddare/DreamCartoonLora",
+    filename="DreamCartoonLora.safetensors"
+)
 
-# Load SDXL base pipeline
+# Load base SDXL pipeline on CPU
 pipe = StableDiffusionXLPipeline.from_pretrained(
     "stabilityai/stable-diffusion-xl-base-1.0",
-    torch_dtype=torch.float16,
-    variant="fp16",
+    torch_dtype=torch.float32,  # Use float32 for CPU
     use_safetensors=True
-).to("cuda")
+).to("cpu")
 
-# Load LoRA
-pipe.load_lora_weights(lora_path)
-
-# Set up scheduler
-pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
+# Load the LoRA weights
+pipe.load_lora_weights(lora_weights)
 
+# Inference function
 def generate(prompt):
-    image = pipe(prompt=prompt).images[0]
+    with torch.no_grad():
+        image = pipe(prompt=prompt).images[0]
     return image
 
-# Gradio UI
+# Simple UI
 gr.Interface(
     fn=generate,
-    inputs=gr.Textbox(label="Prompt"),
+    inputs=gr.Textbox(label="Enter your prompt"),
     outputs="image",
     title="DreamCartoonLora - SDXL 1.0",
-    description="Generate cartoon-style images using a fine-tuned LoRA on SDXL 1.0"
+    description="Cartoon LoRA applied to Stable Diffusion XL 1.0"
 ).launch()
+