Update app.py

app.py

@@ -1,3 +1,33 @@
 import gradio as gr
+import torch
+from transformers import BertTokenizer, BertModel
 
-gr.load("models/google-bert/bert-base-uncased").launch()
+tokenizer = BertTokenizer.from_pretrained('google/bert-base-uncased')
+model = BertModel.from_pretrained('google/bert-base-uncased')
+
+
+def predict(input_text):
+    # Tokenize the input text
+    inputs = tokenizer.encode_plus(
+        input_text,
+        add_special_tokens=True,
+        max_length=512,
+        return_attention_mask=True,
+        return_tensors='pt'
+    )
+
+    # Run the input through the BERT model
+    outputs = model(inputs['input_ids'], attention_mask=inputs['attention_mask'])
+    last_hidden_state = outputs.last_hidden_state[:, 0, :]
+
+    # Return the output (e.g., the pooled output)
+    return last_hidden_state.detach().numpy()
+
+# Create the Gradio app
+app = gr.Interface(
+    fn=predict,
+    inputs="text",
+    outputs="numpy",
+    title="BERT App",
+    description="Enter some text to see the BERT output"
+)