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Backtrack Sampler

An easy-to-understand framework for LLM samplers

Backtrack Sampler is a framework designed for experimenting with custom sampling strategies for language models (LLMs), enabling the ability to rewind and revise generated tokens. It allows developers to create and test their own token generation strategies by providing a base structure for manipulating logits and probabilities, making it a flexible tool for those interested in fine-tuning the behavior of LLMs.

Downloads: 0 This Week

Last Update: 2026-01-07
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