Create app.py

app.py

@@ -0,0 +1,56 @@
+from diffusers import DiffusionPipeline
+import gradio as gr
+import torch
+import math
+
+orig_start_prompt = "A photograph of an adult Lion"
+orig_end_prompt = "A photograph of a Lion cub"
+model_list = ["kakaobrain/karlo-v1-alpha"]
+
+def unclip_text_interpolation(
+  model_path,
+  start_prompt,
+  end_prompt,
+  steps,
+  num_inference_steps
+):
+    
+    pipe = DiffusionPipeline.from_pretrained(model_list, torch_dtype=torch.bfloat16, custom_pipeline='unclip_text_interpolation')
+
+    images = pipe(start_prompt, end_prompt, steps, num_inference_steps=num_inference_steps)
+
+    return images
+
+inputs = [
+  gr.Dropdown(model_list, value=model_list[0], label="Model"),
+  gr.inputs.Textbox(lines=5, default=orig_prompt, label="Start Prompt"),
+  gr.inputs.Textbox(lines=1, default=orig_negative_prompt, label="End Prompt"),
+  gr.inputs.Slider(minimum=2, maximum=12, default=5, step=1, label="Steps")
+]
+
+output = gr.Gallery(
+            label="Generated images", show_label=False, elem_id="gallery"
+        ).style(grid=[int(math.ceil(steps/2))], height="auto")
+
+examples = [
+  ["kakaobrain/karlo-v1-alpha", orig_start_prompt, orig_end_prompt, 6],
+]
+
+title = "UnClip Text Interpolation Pipeline"
+description = """<p>For faster inference without waiting in queue, you may duplicate the space and upgrade to GPU in settings.
+<br/>
+<a href="https://huggingface.co/spaces/kadirnar/stable-diffusion-2-infinite-zoom-out?duplicate=true">
+<img style="margin-top: 0em; margin-bottom: 0em" src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>
+<p/>"""
+
+demo_app = gr.Interface(
+    fn=unclip_text_interpolation,
+    description=description,
+    inputs=inputs,
+    outputs=output,
+    title=title,
+    theme='huggingface',
+    examples=examples,
+    cache_examples=True
+)
+demo_app.launch(debug=True, enable_queue=True)