init commit

app.py

@@ -1,7 +1,31 @@
+from PIL import Image
+from transformers import DonutProcessor, VisionEncoderDecoderModel
+import torch
+import re
 import gradio as gr
+from diffusers import AutoPipelineForText2Image
+import torch
 
-def greet(name):
-    return "Hello " + name + "!!"
+pipeline_text2image = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16")
+pipeline_text2image = pipeline_text2image.to("cuda")
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+
+def text2img(prompt = "A cinematic shot of a baby racoon wearing an intricate italian priest robe.",guidance_scale=0.0, num_inference_steps=1):
+    image = pipeline_text2image(prompt=prompt, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps).images[0]
+    return image
+
+gradio_app_text2img = gr.Interface(
+    fn=text2img,
+    inputs=[
+        gr.Text(),
+        gr.Slider(0.0, 10.0, value=1,step=0.1),
+        gr.Slider(0.0, 10.0, value=1,step=1)
+    ],
+    outputs="image",
+)
+
+
+demo = gr.TabbedInterface([gradio_app_text2img], ["text2img"])
+
+if __name__ == "__main__":
+    demo.launch()