Delete app.py

app.py

@@ -1,49 +0,0 @@
-from distutils.command.upload import upload
-from io import StringIO
-import pandas as pd
-import streamlit as st
-
-from transformers import AutoTokenizer, TFAutoModelForQuestionAnswering
-
-
-@st.cache
-def load_data(file):
-    df = pd.read_csv(file, encoding='utf-8', nrows=50)
-    return df
-
-
-@st.cache
-def load_model_tokenizer():
-    tokenizer_cp = "albert-base-v2"
-    model_cp = "aidan-o-brien/recipe-improver"
-    tokenizer = AutoTokenizer.from_pretrained(tokenizer_cp)
-    model = TFAutoModelForQuestionAnswering.from_pretrained(model_cp)
-    return model, tokenizer
-
-
-# Page config
-title = "Recipe Improver"
-icon = "🍣"
-st.set_page_config(page_title=title, page_icon=icon)
-st.title(title)
-
-# Load csv
-uploaded_file = st.file_uploader("Choose a csv file", type="csv", key='file_uploader')
-if uploaded_file is not None:
-    df = load_data(uploaded_file)
-    st.write(df.head())
-
-# Load tokenizer and model
-model, tokenizer = load_model_tokenizer()
-st.write("Model and tokenizer successfully loaded.")
-
-# Pre-process data from csv file
-
-
-# Run inference
-
-
-# Post-process output of model
-
-
-# Present results