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Awesome GitHub RepositoriesInference Sampling Strategies
Methods for generating and selecting optimal model outputs through aggregation and reward-based evaluation.
Distinguishing note: Focuses on the selection logic at inference time rather than general model generation.
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- stanfordnlp/dspy
stanfordnlp/dspy
32,291View on GitHubDSPy is a declarative programming framework designed for building complex language model applications. It treats model interactions as modular, composable programs, allowing developers to define task logic through typed class schemas rather than relying on manually written prompts. By organizing workflows into hierarchical, reusable Python objects, the framework enables the construction of sophisticated AI systems that manage state and execution flow independently. The framework distinguishes itself through an automated optimization engine that iteratively refines prompt instructions and few-
Generates multiple results and selects the best candidate based on custom reward functions.
Python
