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"""Job-coach-testing-site-zeroshot.ipynb |
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Automatically generated by Colaboratory. |
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Original file is located at |
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https://colab.research.google.com/github/vanderbilt-data-science/job-coach-question-answering/blob/111-create-a-gradio-hf-space-to-test-whether-specific-information-is-in-a-coaching-document/job-coach-testing-zeroshot.ipynb |
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""" |
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import gradio as gr |
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import torch |
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from transformers import AutoTokenizer, AutoModelForQuestionAnswering |
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from transformers import pipeline |
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classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli") |
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question_answerer = pipeline("question-answering", model = "bert-large-uncased-whole-word-masking-finetuned-squad") |
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def zshot(context, queries): |
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answered=[] |
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res=[] |
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notAnswered=[] |
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queries=queries.split("?") |
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queries.pop(-1) |
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for query in queries: |
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query.strip() |
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result = question_answerer(question = query, context=context) |
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answered.append([query,result['answer']]) |
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for item in answered: |
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result = ([text, classifier(text, item[0])]) |
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if result[1]['scores'][0] > 0.01: |
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res.append(item[0] +"? Answer: " + item[1]) |
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else: |
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notAnswered.append(item[0]) |
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result1=''', |
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'''.join(res) |
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result1='''Information Included in the Document: |
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'''+ result1 |
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result2=''', |
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'''.join(notAnswered) |
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result2=''' |
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Information not included in the document, on no clearly stated: |
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'''+ result2 |
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return result1 + result2 |
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app = gr.Interface( |
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zshot, |
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inputs=[ |
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gr.Textbox(label="Context", value=""), |
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gr.Textbox(label="Queries", value=""), |
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], |
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outputs=["text"], |
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) |
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app.launch() |
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"""#### Examples""" |
