| | |
| |
|
| | |
| |
|
| | import gradio as gr |
| | from transformers import pipeline |
| |
|
| | """# Loading Model Name""" |
| |
|
| | model_name = "deepset/roberta-base-squad2" |
| |
|
| | """# Get Predictions |
| | |
| | """ |
| |
|
| | nlu = pipeline('question-answering', model=model_name, tokenizer=model_name) |
| |
|
| | def func(context, question): |
| | input = { |
| | 'question':question, |
| | 'context':context |
| | } |
| | res = nlu(input) |
| | return res["answer"] |
| |
|
| | descr = "This is a question and Answer Web app, you give it a context and ask it questions based on the context provided" |
| |
|
| | app = gr.Interface(fn=func, inputs=[gr.inputs.Textbox(lines=3, placeholder="put in your context here..."),"text"], outputs="text", title="Question Answer App", description=descr) |
| |
|
| | app.launch() |
