Namespace LMKit.TextGeneration.Sampling

Grammar: Represents a grammar class used in text generation models to define and manage grammar rules. This class provides functionalities for creating grammars, managing rules, and controlling token sampling.

GreedyDecoding: Handles greedy decoding strategy.
This algorithm selects the token with the highest probability, ensuring complete determinism.

LogitBias: Handles the rules for applying logit bias during token sampling.
Logit bias enables the prevention of specific text chunks or provides guidance to increase or decrease the likelihood of a word appearing.

Mirostat2Sampling: Specifies the Mirostat sampling strategy in version 2, a neural text decoding algorithm that directly controls perplexity.
Mirostat is a sophisticated algorithm designed to proactively uphold the quality of generated text within a predefined range throughout the text generation process.
It endeavors to achieve a harmonious equilibrium between coherence and diversity, skillfully sidestepping the pitfalls of subpar output resulting from either excessive repetition, commonly referred to as "boredom traps," or lapses in coherence, known as "confusion traps."
The Mirostat algorithm is described in the paper https://arxiv.org/abs/2007.14966

MirostatSampling: Specifies the Mirostat sampling strategy, a neural text decoding algorithm that directly controls perplexity.
Mirostat is a sophisticated algorithm designed to proactively uphold the quality of generated text within a predefined range throughout the text generation process.
It endeavors to achieve a harmonious equilibrium between coherence and diversity, skillfully sidestepping the pitfalls of subpar output resulting from either excessive repetition, commonly referred to as "boredom traps," or lapses in coherence, known as "confusion traps."
The Mirostat algorithm is described in the paper https://arxiv.org/abs/2007.14966

RandomSampling: Handles random sampling strategy (also known as temperature-based sampling).

RepetitionPenalty: Handles the rules for repetition penalties applied during text completion.

Grammar.PredefinedGrammar: Defines the types of predefined grammar rules available for use in text generation.

LogitBiasSetMode: Defines the modes for updating bias values in a bias configuration.

RandomSampling.RandomSamplers: Provides a comprehensive overview of the assortment of samplers available for implementation within the RandomSampling strategy, each offering unique selection mechanisms.