Pinned Repositories
bevfusion
[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
data-efficient-gans
[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
efficientvit
EfficientViT is a new family of vision models for efficient high-resolution vision.
llm-awq
[MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
once-for-all
[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment
proxylessnas
[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
smoothquant
[ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
streaming-llm
[ICLR 2024] Efficient Streaming Language Models with Attention Sinks
temporal-shift-module
[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding
torchquantum
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers.
MIT HAN Lab's Repositories
mit-han-lab/streaming-llm
[ICLR 2024] Efficient Streaming Language Models with Attention Sinks
mit-han-lab/bevfusion
[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
mit-han-lab/temporal-shift-module
[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding
mit-han-lab/llm-awq
[MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
mit-han-lab/once-for-all
[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment
mit-han-lab/efficientvit
EfficientViT is a new family of vision models for efficient high-resolution vision.
mit-han-lab/proxylessnas
[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware
mit-han-lab/data-efficient-gans
[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training
mit-han-lab/torchquantum
A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers.
mit-han-lab/torchsparse
[MICRO'23, MLSys'22] TorchSparse: Efficient Training and Inference Framework for Sparse Convolution on GPUs.
mit-han-lab/gan-compression
[CVPR 2020] GAN Compression: Efficient Architectures for Interactive Conditional GANs
mit-han-lab/smoothquant
[ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
mit-han-lab/anycost-gan
[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing
mit-han-lab/tinyengine
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory
mit-han-lab/tinyml
mit-han-lab/fastcomposer
FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention
mit-han-lab/TinyChatEngine
TinyChatEngine: On-Device LLM Inference Library
mit-han-lab/distrifuser
[CVPR 2024 Highlight] DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models
mit-han-lab/amc
[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices
mit-han-lab/mcunet
[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning
mit-han-lab/tiny-training
On-Device Training Under 256KB Memory [NeurIPS'22]
mit-han-lab/offsite-tuning
Offsite-Tuning: Transfer Learning without Full Model
mit-han-lab/litepose
[CVPR'22] Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation
mit-han-lab/qserve
QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving
mit-han-lab/flatformer
[CVPR'23] FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer
mit-han-lab/patch_conv
Patch convolution to avoid large GPU memory usage of Conv2D
mit-han-lab/lmquant
mit-han-lab/sparsevit
[CVPR'23] SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer
mit-han-lab/spatten-llm
[HPCA'21] SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning
mit-han-lab/tinychat-tutorial