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from transformers import pipeline |
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import pandas as pd |
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tqa = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-wtq") |
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tsqa = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-sqa") |
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mstqa = pipeline(task="table-question-answering", model="microsoft/tapex-large-finetuned-wikisql") |
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mswtqa = pipeline(task="table-question-answering", model="microsoft/tapex-large-finetuned-wtq") |
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table2 = pd.read_excel("/content/Sample.xlsx").astype(str) |
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table3 = table2.head(20) |
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table3 |
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table4 |
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query = "what is the highest delta onu rx power?" |
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query2 = "what is the lowest delta onu rx power?" |
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query3 = "what is the most frequent login id?" |
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query4 = "how many rows with nan values are there?" |
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query5 = "how many S2 values are there" |
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result = tsqa(table=table3, query=query5)["answer"] |
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result |
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from collections import Counter |
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Counter(result) |
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mswtqa(table=table3, query=query5)["answer"] |
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def main(filepath, query): |
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table5 = pd.read_excel(filepath).head(20).astype(str) |
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result = tsqa(table=table5, query=query)["answer"] |
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return result |
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import gradio as gr |
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iface = gr.Interface( |
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fn=main, |
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inputs=[ |
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gr.File(type="filepath", label="Upload XLSX file"), |
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gr.Textbox(type="text", label="Enter text"), |
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], |
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outputs=[gr.Textbox(type="text", label="Text Input Output")], |
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title="Multi-input Processor", |
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description="Upload an XLSX file and/or enter text, and the processed output will be displayed.", |
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) |
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iface.launch() |
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import os |
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import subprocess |
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subprocess.run(["jupyter", "nbconvert", "--to", "script", "--format", "script", "--output", "/content/", "/content/drive/MyDrive/Colab Notebooks/NEW TableQA-GRADIO: Hello World.ipynb"]) |
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