Spaces:
Runtime error
Runtime error
| import gradio as gr | |
| from transformers import pipeline | |
| nlp_qa = pipeline( | |
| 'question-answering', | |
| model='mrm8488/umberto-wikipedia-uncased-v1-finetuned-squadv1-it', | |
| tokenizer='mrm8488/umberto-wikipedia-uncased-v1-finetuned-squadv1-it' | |
| ) | |
| def start(question, context): | |
| response = nlp_qa({ | |
| 'question': question, | |
| 'context': context | |
| }) | |
| text_hilight_output = [ | |
| (context[:response['start']], None), | |
| (context[response['start']:response['end']], 'Answer'), | |
| (context[response['end']:], None) | |
| ] | |
| return text_hilight_output, response['answer'], {response['answer']: response['score']} | |
| face = gr.Interface( | |
| fn=start, | |
| inputs=[ | |
| gr.inputs.Textbox(lines=1, placeholder="Question Here… "), | |
| gr.inputs.Textbox(lines=10, placeholder="Context Here… ") | |
| ], | |
| outputs=[ | |
| gr.outputs.HighlightedText(label='Context'), | |
| gr.outputs.Textbox(label="Answer"), | |
| gr.outputs.Label(num_top_classes=1, label='Score'), | |
| ] | |
| ) | |
| face.launch() |