xyz

app.py

@@ -3,15 +3,21 @@ import numpy as np
 import random
 from diffusers import DiffusionPipeline
 import torch
+from huggingface_hub import login
+import os
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
+# Set your Hugging Face token
+HUGGINGFACE_TOKEN = os.getenv("HUGGINGFACE_TOKEN", "your_huggingface_token")
+login(token=HUGGINGFACE_TOKEN)
+
 # Path to your model repository and safetensors weights
 base_model_repo = "stabilityai/stable-diffusion-3-medium-diffusers"
 lora_weights_path = "./pytorch_lora_weights.safetensors"
 
 # Load the base model
-pipeline = DiffusionPipeline.from_pretrained(base_model_repo, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32)
+pipeline = DiffusionPipeline.from_pretrained(base_model_repo, torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32, use_auth_token=HUGGINGFACE_TOKEN)
 pipeline.load_lora_weights(lora_weights_path)
 pipeline.enable_sequential_cpu_offload()
 pipeline = pipeline.to(device)