Lets explore Large Language Models and how to build one.
Introduction
First things First.Building a Large Language Model (LLM) involves using various tools and packages for data processing, model architecture, training, and evaluation.
Stage 1: Data Preparation and Sampling
Python: The programming language for the entire process.
Pandas: For data manipulation and cleaning.
NLTK (Natural Language Toolkit) or Spacy: For advanced natural language processing tasks like tokenization and part-of-speech tagging.
TensorFlow or PyTorch: The choice between TensorFlow and PyTorch often depends on personal preference or the existing infrastructure, as both are powerful frameworks for deep learning.
Apache AGE For enhancing easy data insight identification.
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