Create app.py

New sentiment analysis

app.py

@@ -0,0 +1,36 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
+
+# Load model
+MODEL = "cardiffnlp/twitter-roberta-base-sentiment-latest"
+tokenizer = AutoTokenizer.from_pretrained(MODEL)
+model = AutoModelForSequenceClassification.from_pretrained(MODEL)
+sentiment_model = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
+
+# Function for Gradio
+def analyze_sentiment(text):
+    result = sentiment_model(text)[0]
+    return {
+        "Sentiment": result["label"],
+        "Confidence": f"{result['score']:.2f}"
+    }
+
+# Example texts
+examples = [
+    ["I absolutely love this new phone, the camera is stunning!"],
+    ["I hate the way this app keeps crashing."],
+    ["It’s fine, nothing special but not terrible either."],
+] 
+
+# Gradio UI
+demo = gr.Interface(
+    fn=analyze_sentiment,
+    inputs=gr.Textbox(lines=3, placeholder="Type a sentence here..."),
+    outputs="label",
+    examples=examples,
+    title="Tweet Sentiment Analyzer",
+    description=""
+)
+
+if _name_ == "_main_":
+    demo.launch()