Delete app.py

app.py

@@ -1,31 +0,0 @@
-import gradio as gr
-from transformers import BertForQuestionAnswering
-from transformers import BertTokenizerFast
-import torch
-
-device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-tokenizer = BertTokenizerFast.from_pretrained('bert-base-uncased')
-model = BertForQuestionAnswering.from_pretrained("CountingMstar/ai-tutor-bert-model").to(device)
-
-def get_prediction(context, question):
-    inputs = tokenizer.encode_plus(question, context, return_tensors='pt').to(device)
-    outputs = model(**inputs)
-    
-    answer_start = torch.argmax(outputs.start_logits)
-    answer_end = torch.argmax(outputs.end_logits) + 1
-    
-    answer = tokenizer.convert_tokens_to_string(tokenizer.convert_ids_to_tokens(inputs['input_ids'][0][answer_start:answer_end]))
-    
-    return answer
-
-def question_answer(context, question):
-    prediction = get_prediction(context, question)
-    return prediction
-
-iface = gr.Interface(
-    fn=question_answer,
-    inputs=[gr.Textbox("Context"), gr.Textbox("Question")],
-    outputs=gr.Textbox("Answer")
-)
-
-iface.launch()