1 dépôt
Awesome GitHub RepositoriesGenerative Training Data Pipelines
Standardized interfaces for feeding large-scale image-label pairs into model training loops.
Distinguishing note: Existing candidates focus on geospatial maps or general key-value mapping, not generative AI training data streams.
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Awesome Generative Training Data Pipelines GitHub Repositories
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- stability-ai/generative-models
Stability-AI/generative-models
27,189Voir sur GitHubThis is a framework for training and sampling diffusion models to generate high-fidelity images, video, and 4D assets. It provides a modular environment for managing generative AI training pipelines, including the handling of datasets, noise sampling, and loss weighting to stabilize the creation of synthetic content. The project features a modular model configuration system that uses YAML-based assembly to define network submodules and conditioners. It also includes a dedicated toolset for AI image watermarking, allowing for the embedding and detection of invisible markers to verify the origi
Ships a map-style data pipeline to efficiently feed large-scale image and label pairs into the training loop.
Python
