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A generative world for general-purpose robotics & embodied AI learning.
A high-performance Python-based I/O system for large (and small) deep learning problems, with strong support for PyTorch.
Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.
Scaling Diffusion Transformers with Mixture of Experts
Official implementation of "Art-Free Generative Models: Art Creation Without Graphic Art Knowledge"
PyTorch native quantization and sparsity for training and inference
D-Adaptation for SGD, Adam and AdaGrad
基于Clash Core 制作的Clash For Linux备份仓库 A Clash For Linux Backup Warehouse Based on Clash Core
Google Research
Schedule-Free Optimization in PyTorch
Visual Instruction-guided Explainable Metric. Code for "Towards Explainable Metrics for Conditional Image Synthesis Evaluation" (ACL 2024 main)
A curated list of papers of interesting empirical study and insight on deep learning. Continually updating...
📚 Collection of awesome generation acceleration resources.
Janus-Series: Unified Multimodal Understanding and Generation Models
A collection of awesome text-to-image generation studies.
Modified h5tool.py make user getting celeba-HQ easier
This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily a…
A library for calculating the FLOPs in the forward() process based on torch.fx
The calflops is designed to calculate FLOPs、MACs and Parameters in all various neural networks, such as Linear、 CNN、 RNN、 GCN、Transformer(Bert、LlaMA etc Large Language Model)
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
High-fidelity performance metrics for generative models in PyTorch
The example of correspondence between fine classes and superclass (coarse class) in ImageNet.
A collection of papers on diffusion models for 3D generation.
Implementation of "SVDiff: Compact Parameter Space for Diffusion Fine-Tuning"