Top K

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Top K sampling is a text generation strategy in which the model considers only the top 'K' most likely next tokens for its next word prediction. By restricting the pool of possible tokens, this method ensures the generated content remains coherent and contextually relevant.

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Tensor Parallelelism

Context Length

Rate Limits

HIPPA

Docker

Llava

Containerized

Public Cloud

Virtual Private Cloud (VPC)

Self-hosted models

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API-based large language models

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CI/CD Pipelines

Kubernetes

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Inference

Inference Server

Mixture of Expert Models (MoE)

Continuous batching

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Zero shot learning

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Transformer

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Transfer learning

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TPU

Top P

Top K

Tokenization

Token

Throughput

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Supervised learning

Serving

Speculative decoding

Sentiment analysis

Sampling temperature

Rust

Recurrent neural network (RNN)

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Prompt engineering

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Ngram

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LLaMA

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Large language model

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Kernel

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Hallucination

GPT

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