phi-2-ft / pre-processing.py
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from datasets import load_dataset
from datasets import load_from_disk
import pandas as pd
from huggingface_hub import interpreter_login
interpreter_login()
# dataset = load_from_disk("Path to folder")
dataset = load_dataset("tatvamasi/medquad-std", split="train")
print(dataset)
# Convert to DataFrame
df = pd.DataFrame(dataset)
# Display the first few rows of the DataFrame
print(df.head(2))
# Need to merge the question and answer in the instruction format
def format_row(row):
question = row['Question']
answer = row['Answer']
formatted_string = f"[INST] {question} [/INST] {answer} "
return formatted_string
# Apply the function to each row of the dataframe
df['Formatted'] = df.apply(format_row, axis=1)
# Display the formatted column
print(df['Formatted'])
new_df = df.rename(columns={'Formatted': 'Text'})
new_df = new_df[['Text']]
print(new_df.head(3))
new_df.to_csv('formatted_qna_set.csv', index=False)
df_from_disk = pd.read_csv("formatted_qna_set.csv")
print(df_from_disk.head(2))