Add application file

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+
+import torch
+from transformers import BertForSequenceClassification, BertTokenizer
+
+# load model
+tokenizer = BertTokenizer.from_pretrained("uget/sexual_content_dection")
+model = BertForSequenceClassification.from_pretrained("uget/sexual_content_dection")
+
+def predict(text):
+    encoding = tokenizer(text, return_tensors="pt")
+    encoding = {k: v.to(model.device) for k,v in encoding.items()}
+
+    outputs = model(**encoding)
+    probs = torch.sigmoid(outputs.logits)
+    
+    predictions = torch.argmax(probs, dim=-1)
+    label_map = {0: "None", 1: "Sexual"}
+    predicted_label = label_map[predictions.item()]
+    print(f"Predictions:{predictions.item()}, Label:{predicted_label}")
+    return {"predictions": predictions.item(), "label": predicted_label}
+
+def greet(name):
+    print("Hello " + name + "!!")
+    return "Hello " + name + "!!"
+
+demo = gr.Interface(fn=predict, inputs="text", outputs="text")
+demo.launch(share=True)