Update app.py

app.py

@@ -1,3 +1,30 @@
 import gradio as gr
+from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
 
-gr.Interface.load("models/NimaKL/FireWatch_tiny_75k").launch()
+model_name = "models/NimaKL/FireWatch_tiny_75k"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+def predict(text):
+    inputs = tokenizer(text, return_tensors="pt")
+    outputs = model(**inputs)
+    logits = outputs.logits
+    label_id = logits.argmax(axis=1).item()
+    return "likely" if label_id == 1 else "unlikely"
+
+io = gr.Interface(
+    fn=predict,
+    inputs="text",
+    outputs="text",
+    title="FireWatch",
+    description="Predict whether a given text describes a fire hazard or not.",
+    output_description="Prediction",
+    examples=[
+        ["Dry and windy weather can increase the risk of wildfires."],
+        ["It is unlikely that a fire will start in this area."]
+    ],
+    output_component_names=["Prediction"],
+    theme="compact"
+)
+
+io.launch()