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What key terms and concepts should one understand when working with LLMs?
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Answer Posted / Beeram Singh
Some key terms and concepts that are important to understand when working with Language Models (LLMs) include:
1. Corpus: A collection of text data used for training an LLM.
2. Tokenization: The process of breaking down text into individual tokens or words.
3. Embedding: A representation of a token as a high-dimensional vector in a continuous space.
4. Transformer architecture: A neural network architecture commonly used for building LLMs, designed to handle long sequences of data efficiently.
5. Fine-tuning: The process of further training an existing pre-trained model on a specific task or dataset.
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