Create app.py

app.py

@@ -0,0 +1,16 @@
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import gradio as gr
+import torch
+
+model = AutoModelForSequenceClassification.from_pretrained("my-flava-model")
+tokenizer = AutoTokenizer.from_pretrained("my-flava-model")
+
+def classify_text(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+    with torch.no_grad():
+        outputs = model(**inputs)
+    prediction = torch.argmax(outputs.logits, dim=1).item()
+    return str(prediction)
+
+iface = gr.Interface(fn=classify_text, inputs="text", outputs="text")
+iface.launch()