Create app.py

app.py

@@ -0,0 +1,26 @@
+import gradio as gr
+import torch
+from transformers import pipeline
+
+model_ckpt = "HenryAI/KerasBERTv1"
+fill_mask = pipeline("fill-mask", model=model_ckpt)  
+
+
+def  cloze_task(text):
+    preds = fill_mask(text)     
+    return preds
+    
+    
+answer = []      
+description="Let's see if BERT has learnt how to write Keras!"
+title="Keras BERT v1",
+gradio_ui = gr.Interface(fn= cloze_task,
+    title= title, description = description,
+    inputs=[gr.inputs.Textbox(lines=3)],
+    outputs=[gr.outputs.Textbox(label="Answer"),],
+    examples=[["from tensorflow.keras import [MASK]"],],
+    enable_queue=True
+)
+gradio_ui.launch(debug=True)
+
+