Create app.py

app.py

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+import streamlit as st
+from PIL import Image
+from transformers import pipeline
+
+# Load your fine-tuned zero-shot model
+classifier = pipeline("zero-shot-classification", model="Balajim57/zero-shot-vitb32")
+
+def predict(image, prompt1, prompt2, prompt3):
+    # Perform zero-shot classification on the uploaded image with provided prompts
+    results = classifier(image, [prompt1, prompt2, prompt3])
+    return results["labels"]
+
+# Streamlit UI components
+st.title("Zero-Shot Image Classification")
+uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+prompt1 = st.text_input("Prompt 1")
+prompt2 = st.text_input("Prompt 2")
+prompt3 = st.text_input("Prompt 3")
+if uploaded_image:
+    image = Image.open(uploaded_image)
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+    if st.button("Classify"):
+        results = predict(image, prompt1, prompt2, prompt3)
+        st.write("Classification Results:")
+        st.write(results)