Update app.py

app.py

@@ -1,15 +1,20 @@
 import gradio as gr
-from transformers import pipeline
+import torch
+import torchvision
+from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler
 
-pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
+model_id = "stabilityai/stable-diffusion-2"
 
-def predict(image):
-    predictions = pipeline(image)
-    return {p["label"]: p["score"] for p in predictions}
+# Use the Euler scheduler here instead
+scheduler = EulerDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
+pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=scheduler, torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
 
-gr.Interface(
-    predict,
-    inputs=gr.inputs.Image(label="Upload hot dog candidate", type="filepath"),
-    outputs=gr.outputs.Label(num_top_classes=2),
-    title="Hot Dog? Or Not?",
-).launch()
+@gr.inputs(text="Enter a sentence to classify its sentiment (type 'exit' to quit)")
+@gr.outputs(image="Output image")
+def classify_sentiment(prompt):
+  image = pipe(prompt).images[0]
+  image.save("output/" + prompt + ".png")
+  image.show()
+
+gr.Interface(classify_sentiment).launch()