This tutorial covers fine-tuning BERT for sentiment analysis using Hugging Face Transformers. Learn to prepare data, set up environment, train and evaluate the model, and make predictions.
Discusses the trends in Large Language Models (LLMs) architecture, including the rise of more GPU, more weights, more tokens, energy-efficient implementations, the role of LLM routers, and the need for better evaluation metrics, faster fine-tuning, and self-tuning.
Delving into transformer networks
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