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Back to sdv-dev/sdgym

Open-source alternatives to SDGym

17 open-source projects similar to sdv-dev/sdgym, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best SDGym alternative.

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    facebookresearch/flow_matching

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    This project is a PyTorch-based generative model framework designed to transform noise into complex data distributions by learning vector fields and probability paths. It serves as a multimodal generative toolkit for producing synthetic text and images through learned probability flows. The library distinguishes itself by supporting continuous, discrete, and Riemannian manifold integrations. This allows the framework to handle a variety of data types, including categorical data via discrete-state flow matching and non-Euclidean spaces through Riemannian manifold integration. The toolkit cove

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    2022-1-5: Our new work (ScriptWriter-CPre) has been accepted by TOIS! - 2021-10-19: We upload the code and data for our new model ScriptWriter-CPre. - 2020-06-11: We find a minor error in the data thus we upload a new one. We provide the code for building data file from text file. You can now…

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    This project is a deep learning poetry generator designed to create traditional Chinese couplets. It utilizes a sequence-to-sequence neural network architecture to map input text sequences to matching output sequences, functioning as a text generation model and an inference web service. The system features a neural text ranking mechanism that evaluates candidate outputs based on length consistency and character patterns to ensure structural alignment. It also includes a content filtering process that scans generated text against forbidden word lists to remove sensitive or inappropriate materi

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  • xianhu/learnpythonxianhu 的头像

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    LearnPython is a programming tutorial consisting of a collection of practical code examples used to demonstrate Python language features and programming patterns. It serves as a comprehensive learning resource that implements core language concepts through functional code. The project provides specialized guides and samples covering several key domains. These include asynchronous network programming with event loops and coroutines, data visualization using numerical datasets for 2D and 3D plots, and web scraping for fetching content and automating login flows. It also features instructions on

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