AI說書 - 從0開始 - 181 | 預訓練模型資料下載與相關依賴準備

我想要一天分享一點「LLM從底層堆疊的技術」，並且每篇文章長度控制在三分鐘以內，讓大家不會壓力太大，但是又能夠每天成長一點。

• AI說書 - 從0開始 - 180 | RoBERTa 預訓練前言：RoBERTa 預訓練前言

這次預訓練模型使用的資料集為 Kaggle’s Customer Support on Twitter dataset，詳見 https://www.kaggle.com/datasets/thoughtvector/customer- support-on-twitter

過程需要有 Kaggle 帳戶，前置作業如下：

from google.colab import drive 
drive.mount('/content/drive')

import os 
import json 

try: 
	import kaggle 
except: 
	!pip install kaggle 
	import kaggle

with open(os.path.expanduser("drive/MyDrive/files/kaggle.json"), "r") as f: 
	kaggle_credentials = json.load(f) 
	
kaggle_username = kaggle_credentials["username"] 
kaggle_key = kaggle_credentials["key"] 
os.environ["KAGGLE_USERNAME"] = kaggle_username 
os.environ["KAGGLE_KEY"] = kaggle_key
kaggle.api.authenticate()

!kaggle datasets download -d thoughtvector/customer-support-on-twitter

然後執行解壓縮過程：

import zipfile

with zipfile.ZipFile('/content/customer-support-on-twitter.zip', 'r') as zip_ref: 
	zip_ref.extractall('/content/') 
	print("File Unzipped!")

接著來安裝相關配件包：

!pip install accelerate == 0.29.3 
!pip install Transformers == 4.40.1 
!pip install datasets == 2.16.0 #installing Hugging Face datasets for data loading and preprocessing 
from accelerate import Accelerator