Update app.py

app.py

@@ -12,11 +12,12 @@ from huggingface_hub import hf_hub_download
 # The base model your LoRA was trained on.
 base_model_id = "stabilityai/stable-diffusion-xl-base-1.0"
 
+# --- CORRECTED REPOSITORY PATH ---
 # The path to your LoRA file on the Hugging Face Hub.
-lora_repo_id = "TuringsSolutions/EmilyH"
+lora_repo_id = "TuringSolutions/EmilyH"  # Corrected from "TuringsSolutions"
 lora_filename = "emilyh.safetensors"
 
-# --- Load the Pipeline ---
+# --- Load the Pipeline (No token needed for public repos) ---
 # Use a recommended VAE for SDXL
 vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
 pipe = StableDiffusionXLPipeline.from_pretrained(
@@ -27,21 +28,15 @@ pipe = StableDiffusionXLPipeline.from_pretrained(
     use_safetensors=True
 )
 
-# --- Load and Fuse the LoRA ---
+# --- Load and Fuse the LoRA (No token needed for public repos) ---
 # Download the LoRA file and load the state dict.
 lora_file_path = hf_hub_download(repo_id=lora_repo_id, filename=lora_filename)
 pipe.load_lora_weights(lora_file_path)
 
-# It's recommended to fuse the LoRA weights for better performance,
-# but this is optional. You can also use pipe.set_adapters(["default"], adapter_weights=[0.9])
-# during inference if you prefer more dynamic control.
-# pipe.fuse_lora(lora_scale=0.9) # Fusing is more efficient
-
 # Move the pipeline to the GPU
 pipe.to("cuda")
 
 # --- Default Settings from your Recommendations ---
-# These are pulled directly from your "Recomendations.txt".
 default_positive_prompt = "masterpiece, best quality, ultra-detailed, realistic skin, intricate details, highres"
 default_negative_prompt = "low quality, worst quality, blurry, (deformed:1.3), extra fingers, cartoon, 3d, anime, bad anatomy"
 default_sampler = "DPM++ 2M Karras"
@@ -79,7 +74,7 @@ def generate_image(prompt, negative_prompt, sampler, steps, cfg, width, height,
         guidance_scale=cfg,
         num_inference_steps=steps,
         generator=generator,
-        cross_attention_kwargs={"scale": 0.9} # This is an alternative way to apply LoRA scale if not fused
+        cross_attention_kwargs={"scale": 0.9} 
     ).images[0]
 
     return image