Add application file

app.py

@@ -1,16 +1,19 @@
 
-from diffusers import LDMTextToImagePipeline
+from diffusers import LDMTextToImagePipeline,DiffusionPipeline
 import gradio as gr
 import PIL.Image
 import numpy as np
 import random
 import torch
+from transformers import eBart
+model = eBart.from_pretrained("dalle-mini/dalle-mega")
+ldm_pipeline = DiffusionPipeline.from_pretrained("dalle-mini/dalle-mega")
 
-ldm_pipeline = LDMTextToImagePipeline.from_pretrained("dalle-mini/dalle-mega")
 
 def predict(prompt, steps=100, seed=42, guidance_scale=6.0):
     torch.cuda.empty_cache()
     generator = torch.manual_seed(seed)
+    img = model([prompt])
     images = ldm_pipeline([prompt], generator=generator, num_inference_steps=steps, eta=0.3, guidance_scale=guidance_scale)["sample"]
     return images[0]