Official PyTorch Implementation of MambaVision: A Hybrid Mamba-Transformer Vision Backbone

A novel implementation of fusing ViT with Mamba into a fast, agile, and high performance Multi-Modal Model. Powered by Zeta, the simplest AI framework ever.

Implementation of Vision Mamba from the paper: "Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model" It's 2.8x faster than DeiT and saves 86.8% GPU memory when performing batch inference to extract features on high-res images

PointMamba: A Simple State Space Model for Point Cloud Analysis

[IEEE TGRS 2024] ChangeMamba: Remote Sensing Change Detection Based on Spatio-Temporal State Space Model

The fast conda package builder, based on mamba

A PyTorch implementation of the paper "ZigMa: A DiT-Style Mamba-based Diffusion Model" (ECCV 2024)

The libmamba based solver for conda.

Offical Code of MICCAI'24 early accepted paper "LGRNet: Local-Global Reciprocal Network for Uterine Fibroid Segmentation in Ultrasound Videos"

Implementation of MambaByte in "MambaByte: Token-free Selective State Space Model" in Pytorch and Zeta

Mambular is a Python package that brings the power of Mamba architectures to tabular data, offering a suite of deep learning models for regression, classification, and distributional regression tasks. This includes models like Mambular, FT-Transformer, TabTransformer and tabular ResNets.

The official implementation of SSAMBA: Self-Supervised Audio Representation Learning with Mamba State Space Model

Official Implementation of the work "Audio Mamba: Bidirectional State Space Model for Audio Representation Learning"

Minimal Mamba-2 implementation in PyTorch

Unofficial but Efficient Implementation of "Mamba: Linear-Time Sequence Modeling with Selective State Spaces" in JAX

An efficient pytorch implementation of selective scan in one file, works with both cpu and gpu, with corresponding mathematical derivation. It is probably the code which is the most close to selective_scan_cuda in mamba.

Implementation of PyTorch: "GAMBA: MARRY GAUSSIAN SPLATTING WITH MAMBA FOR SINGLE-VIEW 3D RECONSTRUCTION"

[OpenPAR] An open-source framework for Pedestrian Attribute Recognition, based on PyTorch

T-Mamba: A unified framework with Long-Range Dependency in dual-domain for 2D & 3D Tooth Segmentation