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Julien Simon
commited on
Commit
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54c2f4d
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Parent(s):
cc07d78
Update
Browse files- app.py +25 -13
- requirements.txt +2 -0
app.py
CHANGED
@@ -22,32 +22,40 @@ pipe_tapas = pipeline(
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def process(query, file,
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table = pd.read_csv(file.name, header=0).astype(str)
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table = table[:rows]
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result_tapex = pipe_tapex(table=table, query=query)
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result_tapas = pipe_tapas(table=table, query=query)
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return result_tapex["answer"], result_tapas["answer"]
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# Inputs
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query_text = gr.Text(label="Enter a question")
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input_file = gr.File(label="Upload a CSV file", type="
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rows_slider = gr.Slider(label="Number of rows")
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# Output
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answer_text_tapex = gr.Text(label="TAPEX answer")
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answer_text_tapas = gr.Text(label="TAPAS answer")
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description =
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iface = gr.Interface(
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theme="huggingface",
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"default_file.csv",
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20,
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],
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[
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["What is the average number of wins?", "default_file.csv", 20],
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],
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allow_flagging="never",
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)
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def process(query, file, rows=20):
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table = pd.read_csv(file.name, header=0).astype(str)
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table = table[:rows]
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result_tapex = pipe_tapex(table=table, query=query)
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result_tapas = pipe_tapas(table=table, query=query)
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return result_tapex["answer"], result_tapas["answer"]
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# Inputs
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query_text = gr.Text(label="Enter a question")
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input_file = gr.File(label="Upload a CSV file", type="filepath")
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rows_slider = gr.Slider(label="Number of rows")
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# Output
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answer_text_tapex = gr.Text(label="TAPEX answer")
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answer_text_tapas = gr.Text(label="TAPAS answer")
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description = (
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"This Space lets you ask questions on CSV documents with Microsoft "
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"[TAPEX-Large](https://huggingface.co/microsoft/tapex-large-finetuned-wtq) "
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"and Google [TAPAS-Large](https://huggingface.co/google/tapas-large-finetuned-wtq). "
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"Both have been fine-tuned on the "
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"[WikiTableQuestions](https://huggingface.co/datasets/wikitablequestions) dataset. \n\n"
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"A sample file with football statistics is available in the repository: \n\n"
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"* Which team has the most wins? Answer: Manchester City FC\n"
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"* Which team has the most wins: Chelsea, Liverpool or Everton? Answer: "
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"Liverpool\n"
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"* Which teams have scored less than 40 goals? Answer: Cardiff City FC, "
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"Fulham FC, Brighton & Hove Albion FC, Huddersfield Town FC\n"
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"* What is the average number of wins? Answer: 16 (rounded)\n\n"
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"You can also upload your own CSV file. Please note that maximum sequence "
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"length for both models is 1024 tokens, so you may need to limit the number "
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"of rows in your CSV file. Chunking is not implemented yet."
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)
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iface = gr.Interface(
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theme="huggingface",
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"default_file.csv",
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20,
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],
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[
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"Which teams have scored less than 40 goals?",
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"default_file.csv",
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20
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],
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["What is the average number of wins?", "default_file.csv", 20],
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],
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allow_flagging="never",
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requirements.txt
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transformers
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torch
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transformers
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torch
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gradio
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pandas
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