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README.md

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+---
+title: G3 Tweet Classifier
+emoji: 🔥
+colorFrom: pink
+colorTo: gray
+sdk: gradio
+sdk_version: 5.28.0
+app_file: app.py
+pinned: false
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from transformers import pipeline
+# Load a tweet classification model from Hugging Face
+classifier = pipeline("text-classification", model="finiteautomata/bertweet-base-sentiment-analysis")
+
+def classify_tweet(tweet):
+    result = classifier(tweet)[0]
+    label = result['label']
+    score = result['score']
+    return f"Label: {label} (Confidence: {score:.2f})"
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=classify_tweet,
+    inputs=gr.Textbox(lines=3, placeholder="Enter a tweet here..."),
+    outputs="text",
+    title="Tweet Classifier",
+    description="Enter a tweet and click the button to classify it!"
+)
+
+# Launch the app
+iface.launch()

requirements.txt

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+transformers
+torch
+gradio