Developing an LLM: Building, Training, Finetuning
Read OriginalThis article presents a comprehensive video guide on developing Large Language Models (LLMs). It covers the entire development cycle including architectural implementation, dataset considerations, tokenization, pretraining techniques, finetuning for classification and instruction, preference finetuning, and model evaluation methods with their respective caveats.
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