test

app.py

@@ -8,9 +8,10 @@ from diffusers import StableDiffusionPipeline, DDIMScheduler,  DiffusionPipeline
 import streamlit as st
 
 # model_path = WEIGHTS_DIR             # If you want to use previously trained model saved in gdrive, replace this with the full path of model in gdrive
-headers = {"Authorization": "Bearer xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"}
+# headers = {"Authorization": "Bearer xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"}
 # pipe = StableDiffusionPipeline.from_pretrained("Divyanshu04/Finetuned-sd-vae", safety_checker=None, torch_dtype=torch.float32).to("cuda")
-pipe = DiffusionPipeline.from_pretrained("Divyanshu04/Finetuned-sd-vae", torch_dtype=torch.float32, use_auth_token = headers)
+
+pipe = DiffusionPipeline.from_pretrained("Divyanshu04/Finetuned-sd-vae", torch_dtype=torch.float32, use_auth_token = "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")
 pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
 pipe.enable_xformers_memory_efficient_attention()
 g_cuda = None