Create app.py

app.py

@@ -0,0 +1,35 @@
+from accelerate.utils import write_basic_config
+from diffusers import DiffusionPipeline
+import torch
+import gradio as gr
+
+
+write_basic_config()
+
+base = DiffusionPipeline.from_pretrained(
+    "Mahdy225/JAMAL",
+    torch_dtype=torch.float16,
+    use_safetensors=True
+)
+base.to("cuda")
+
+def text2Image(prompt, steps=50, scale=7, Width=1024, Height=1024):
+    image = base(prompt, num_inference_steps=steps, guidance_scale=scale,
+                 width=Width, height=Height, cross_attention_kwargs={"scale": 1}).images[0]
+    return image
+
+ui = gr.Interface(fn=text2Image,
+                  inputs=[
+                      gr.Textbox(label="Enter Text Prompt"),
+                      gr.Slider(minimum=10, maximum=150, value=50, label="Number of Inference Steps"),
+                      gr.Slider(minimum=4, maximum=10, value=7, step=0.1, label="Guidance Scale"),
+                      gr.Number(label="Image Width", value=1024),
+                      gr.Number(label="Image Height"), value=1024],
+                      outputs="image",
+                      title="JAMAL/چمال: Transforming Words into Reality"
+                  )
+
+# ui.launch(share=True)
+
+if __name__ == "__main__":
+    ui.launch()