SuperNova672's picture
Update app.py
935bae0
raw
history blame
1.37 kB
import gradio as gr
import pandas as pd
from transformers import AutoModelForSeq2SeqLM, AutoModelForTableQuestionAnswering, AutoTokenizer, pipeline
model_tapas = "google/tapas-large-finetuned-wtq"
tokenizer_tapas = AutoTokenizer.from_pretrained(model_tapas)
pipe_tapas = pipeline("table-question-answering", model=model_tapas, tokenizer=tokenizer_tapas)
def process(query, file, correct_answer):
table = pd.read_csv(file.name).astype(str).fillna('')
#table = table[:rows] if rows else table
result_tapas = pipe_tapas(table = table, query = query)
return result_tapas['answer']
query_text = gr.Text(label = "Enter a question")
input_file = gr.File(label = "Upload a CVS file", type = "file")
# outputs from the app
answer_text_tapas = gr.Text(label = "TAPAS answer")
description = """
# Siddharth Test Gradio Table QA
"""
iface = gr.Interface(
theme="huggingface",
description=description,
fn = process,
inputs = [query_text, input_file,],
outputs = [answer_text_tapas],
examples = [["Apps with more than 4.7 rating in art and design?","playstore_text_csv.csv","Harley Quinn wallpapers HD --- ",],
["How many apps have Beauty genres?","playstore_text_csv.csv",""],
["Average Installs of apps with Beauty genres?","playstore_text_csv.csv",""] ]
,
allow_flagging="never"
)
iface.launch()