Python toolkit for building production-ready LLM applications. Modular utilities for prompts, RAG, agents, structured outputs, and multi-provider support.
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Denoising Diffusion Implicit Models, Jiaming Song, Chenlin Meng, Stefano Ermon, 2020International Conference on Learning Representations (ICLR)DOI: 10.48550/arXiv.2010.02502 - The original research paper introducing the DDIM algorithm, detailing its non-Markovian generative process, deterministic sampling, and ability to use subsequences for faster generation.
Score-Based Generative Modeling through Stochastic Differential Equations, Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, Ben Poole, 2021International Conference on Learning Representations (ICLR)DOI: 10.48550/arXiv.2011.13456 - Provides a unifying theoretical framework for diffusion models, including DDPM and DDIM, by connecting them to SDEs and ODEs. This helps understand the theoretical underpinnings of DDIM's deterministic and faster sampling.