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[MICRO'23, MLSys'22] TorchSparse: Efficient Training and Inference Framework for Sparse Convolution on GPUs.
A collection of resources and papers on Vector Quantized Variational Autoencoder (VQ-VAE) and its application
Writing AI Conference Papers: A Handbook for Beginners
PyTorch implementation of MAR+DiffLoss https://arxiv.org/abs/2406.11838
Efficient, check-pointed data loading for deep learning with massive data sets.
HI-ML toolbox for deep learning for medical imaging and Azure integration
Taming Transformers for High-Resolution Image Synthesis
Implementation of Generating Diverse High-Fidelity Images with VQ-VAE-2 in PyTorch
Step-aware Preference Optimization: Aligning Preference with Denoising Performance at Each Step
Export VMamba to onnx. VMamba: Visual State Space Models，code is based on VMamba: https://github.com/MzeroMiko/VMamba
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"
LLaVA-UHD: an LMM Perceiving Any Aspect Ratio and High-Resolution Images
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
[NeurIPS2024 Spotlight] The official implementation of GrootVL: Tree Topology is All You Need in State Space Model
A native PyTorch Library for large model training
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference,…
vHeat: Building Vision Models upon Heat Conduction
End-to-End Object Detection with Transformers
DynRefer: Delving into Region-level Multi-modality Tasks via Dynamic Resolution
An efficient pure-PyTorch implementation of Kolmogorov-Arnold Network (KAN).
MambaOut: Do We Really Need Mamba for Vision?
[ICLR 2023 Spotlight] Vision Transformer Adapter for Dense Predictions
Get up and running with Llama 3.2, Mistral, Gemma 2, and other large language models.