Create app.py

app.py

@@ -0,0 +1,14 @@
+from huggingface_hub import from_pretrained_fastai
+import gradio as gr
+from fastai.text.all import *
+
+learner = load_learner("entrega")
+labels = list(range(0,150))
+
+
+def predict(text):
+    pred,pred_idx,probs = learner.predict(text)
+    return {labels[i]: float(probs[i]) for i in range(len(labels))}
+
+
+gr.Interface(fn=predict, inputs="text", outputs=gr.outputs.Label(num_top_classes=5)).launch(share=False)