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Large Language Model (LLM)

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10 Terms

1

Large Language Model (LLM)

An artificial intelligence model designed to understand and generate human-like text based on vast amounts of training data, typically consisting of billions or trillions of parameters.

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2

Encoder

Part of LLM architectures that encode text into embeddings, converting sequences of words into vectors to capture text semantics or meaning.

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3

Decoder

Component of LLM architectures that decodes or generates text, producing a sequence of words based on input sequences.

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4

Prompting

Providing an initial input or "prompt" to LLMs to guide text generation or task completion based on training data.

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5

In-context learning

Constructing prompts with task demonstrations for LLMs.

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6

Greedy decoding

Decoding technique where the model selects the token with the highest probability at each step of sequence generation.

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7

Retrieval Augmented Generation (RAG)

Approach combining retrieval-based and generative models to enhance text generation with relevant external knowledge.

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8

Vector Databases

Specialized databases for storing and querying high-dimensional vector data, suitable for ML, NLP, and computer vision applications.

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9

Semantic Search

Advanced information retrieval technique focusing on understanding the meaning behind search queries and documents for more accurate results.

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10

OCI Generative AI Service

Oracle Cloud service offering pre-trained LLMs, fine-tuning capabilities, dedicated resources, and flexibility for text-based tasks.

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