Create app.py

app.py

@@ -0,0 +1,33 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import torch
+
+MODEL_NAME = "Unknownaut/entity-level-framing-news-roberta"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSequenceClassification.from_pretrained(MODEL_NAME)
+
+labels = ["Legitimate", "Aggressor", "Defensive", "Neutral"]
+
+def predict(sentence, entity):
+    inputs = tokenizer(
+        sentence,
+        entity,
+        return_tensors="pt",
+        truncation=True,
+        max_length=160
+    )
+
+    with torch.inference_mode():
+        outputs = model(**inputs)
+        pred = torch.argmax(outputs.logits, dim=1).item()
+
+    return labels[pred]
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=["text", "text"],
+    outputs="text"
+)
+
+demo.launch()