1 مستودع
Awesome GitHub RepositoriesGenerative
Datasets created specifically to benchmark the performance of generative models.
Distinct from Evaluation Datasets: Focuses on the generation of visual datasets for benchmarking, not just static collections of inputs for LLMs.
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Awesome Generative GitHub Repositories
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- facebookresearch/dit
facebookresearch/DiT
8,642عرض على GitHubDiT is a latent diffusion model and transformer-based generative AI framework implemented in PyTorch. It functions as a class-conditional image generator that replaces traditional convolutional backbones with a transformer architecture to synthesize high-fidelity images. The project utilizes patch-based latent processing and latent space compression to operate on low-dimensional image representations. It incorporates class-conditional guidance and adjustable guidance scales to control the visual content of generated images during the sampling process. The framework covers distributed model t
Enables parallel generation of large image batches to evaluate model performance across diverse datasets.
Python
