Try model

app.py

@@ -1,16 +1,12 @@
 import gradio as gr
+from transformers import pipeline
+
+checkpoint = "openai/clip-vit-large-patch14"
+detector = pipeline(model=checkpoint, task="zero-shot-image-classification")
 
-"""
-pipe = pipeline("classification", model="openai/clip-vit-large-patch14")
 def classify(img):
-    predictions = pipe(img)
-    pipe(text=["", "a photo of a dog"], images=image, return_tensors="pt", padding=True)
+    predictions = detector(img, candidate_labels=["fox", "bear", "seagull", "owl"])
     return predictions
 
 iface = gr.Interface(fn=classify, inputs="image", outputs="text")
-iface.launch()
-"""
-
-
-iface = gr.load("huggingface/openai/clip-vit-large-patch14")
 iface.launch()