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Unveiling the Complex World of LLM Training: A Deep Dive into the Steps and Best Practices Involved in Training LLMs
A comprehensive overview of the training process of large language models (LLMs). The article explains the intricate steps involved in training LLMs, from data collection and tokenisation to fine-tuning and evaluation. It emphasizes the importance of data diversity, efficient compute use, and ethical considerations in LLM development. The author provides best practices for training LLMs, highlighting the need for a balanced and diverse dataset, efficient computational methods, and attention to ethical implications.

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