Create app.py

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load SST sentiment model (adjust model name if different)
+sst_classifier = pipeline(
+    "text-classification",
+    model="SamanthaStorm/tether-sst",  # replace with your actual SST model name
+    top_k=None,
+    truncation=True
+)
+
+def classify_sentiment(text):
+    result = sst_classifier(text)[0]
+    label = result["label"]
+    score = round(result["score"] * 100, 2)
+
+    if label == "LABEL_0":
+        return f"Supportive ({score}%)"
+    elif label == "LABEL_1":
+        return f"Undermining ({score}%)"
+    else:
+        return f"Unknown label ({label})"
+
+iface = gr.Interface(
+    fn=classify_sentiment,
+    inputs=gr.Textbox(lines=4, placeholder="Paste message here..."),
+    outputs="text",
+    title="Tether SST Sentiment Analyzer",
+    description="Classifies language as Supportive or Undermining based on tone and intent. Part of the Tether project."
+)
+
+iface.launch()