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Raymond King
RaymondKing/
RAG-On-Clinical-Data
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# -*- coding: utf-8 -*-

"""Untitled39.ipynb



Automatically generated by Colab.



Original file is located at

    https://colab.research.google.com/drive/1pcHOb70S4TwkxIKgrNTFfLdc71vMgOKg

"""



import torch

import time

import evaluate

import pandas as pd

import numpy as np

from transformers import DataCollatorForSeq2Seq





from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

from transformers import Seq2SeqTrainingArguments, DataCollatorForSeq2Seq, Seq2SeqTrainer

#from datasets import load_dataset



from google.colab import drive

drive.mount('/content/drive')



import os

folder_path = '/content/drive/My Drive/nosocomial/hapi'

os.chdir(folder_path)

print("Current Directory:", os.getcwd())



hapi_trainLabels = pd.read_csv('train.labels.csv')

hapi_trainChronologies=pd.read_csv('train.chronologies.csv')

hapi_trainLabels=pd.read_csv('train.labels.csv')

hapi_develAdmittimes=pd.read_csv('devel.admittimes.csv')

hapi_develChronologies=pd.read_csv('devel.chronologies.csv')

hapi_develLabels=pd.read_csv('devel.labels.csv')

hapi_negativeLabels=pd.read_csv('negative_labels.csv')

hapi_testAdmittimes=pd.read_csv('test.admittimes.csv')

hapi_testchronologies=pd.read_csv('test.chronologies.csv')

hapi_testLabels =pd.read_csv('test.labels.csv')

hapi_testChronologies =pd.read_csv('test.chronologies.csv')

hapi_testLabels =pd.read_csv('test.labels.csv')



haki_trainLabels = pd.read_csv('train.labels.csv')

haki_trainChronologies=pd.read_csv('train.chronologies.csv')

haki_trainLabels=pd.read_csv('train.labels.csv')

haki_develAdmittimes=pd.read_csv('devel.admittimes.csv')

haki_develChronologies=pd.read_csv('devel.chronologies.csv')

haki_develLabels=pd.read_csv('devel.labels.csv')

haki_negativeLabels=pd.read_csv('negative_labels.csv')

haki_testAdmittimes=pd.read_csv('test.admittimes.csv')

haki_testchronologies=pd.read_csv('test.chronologies.csv')

haki_testLabels =pd.read_csv('test.labels.csv')

haki_testChronologies =pd.read_csv('test.chronologies.csv')

haki_testLabels =pd.read_csv('test.labels.csv')



haa_trainLabels = pd.read_csv('train.labels.csv')

haa_trainChronologies=pd.read_csv('train.chronologies.csv')

haa_develAdmittimes=pd.read_csv('devel.admittimes.csv')

haa_develChronologies=pd.read_csv('devel.chronologies.csv')

haa_develLabels=pd.read_csv('devel.labels.csv')

haa_negativeLabels=pd.read_csv('negative_labels.csv')

haa_testAdmittimes=pd.read_csv('test.admittimes.csv')

haa_testchronologies=pd.read_csv('test.chronologies.csv')

haa_testLabels =pd.read_csv('test.labels.csv')

haa_testChronologies =pd.read_csv('test.chronologies.csv')

haa_testLabels =pd.read_csv('test.labels.csv')







"""####  HAA	C0002871 (Anemia)	anemia, anaemia, HAA	WHO[19]"""



haa_trainChronologies.head()



haa_trainChronologies.head()



haa_develAdmittimes.head()



haa_develChronologies.head()