vokkko

vokkko's Stars

• mlc-ai/mlc-llm

  Universal LLM Deployment Engine with ML Compilation

  Language:Python19.5k1771.4k1.6k

• BradyFU/Awesome-Multimodal-Large-Language-Models

  :sparkles::sparkles:Latest Advances on Multimodal Large Language Models

  13.3k257128840

• OpenBMB/MiniCPM-V

  MiniCPM-V 2.6: A GPT-4V Level MLLM for Single Image, Multi Image and Video on Your Phone

  Language:Python12.9k106612905

• CompVis/latent-diffusion

  High-Resolution Image Synthesis with Latent Diffusion Models

  Language:Jupyter Notebook12.1k973481.6k

• bitsandbytes-foundation/bitsandbytes

  Accessible large language models via k-bit quantization for PyTorch.

  Language:Python6.5k521.1k641

• chaiNNer-org/chaiNNer

  A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.

  Language:Python4.7k64844288

• Fanghua-Yu/SUPIR

  SUPIR aims at developing Practical Algorithms for Photo-Realistic Image Restoration In the Wild. Our new online demo is also released at suppixel.ai.

  Language:Python4.5k65144393

• intel/neural-compressor

  SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime

  Language:Python2.3k33209258

• NVlabs/Sana

  SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer

  Language:Python1.7k638489

• horseee/Awesome-Efficient-LLM

  A curated list for Efficient Large Language Models

  Language:Python1.4k41499

• JDAI-CV/dabnn

  dabnn is an accelerated binary neural networks inference framework for mobile platform

  Language:C++7733829102

• MyNiuuu/MOFA-Video

  [ECCV 2024] MOFA-Video: Controllable Image Animation via Generative Motion Field Adaptions in Frozen Image-to-Video Diffusion Model.

  Language:Python671235343

• mit-han-lab/nunchaku

  SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models

  Language:Cuda547104428

• Cornell-RelaxML/quip-sharp

  Language:Python512126845

• mit-han-lab/duo-attention

  DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads

  Language:Python41381223

• intel/auto-round

  Advanced Quantization Algorithm for LLMs/VLMs.

  Language:Python287126825

• efeslab/Atom

  [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving

  Language:Cuda281102025

• facebookresearch/SpinQuant

  Code repo for the paper "SpinQuant LLM quantization with learned rotations"

  Language:Python19482019

• Guangxuan-Xiao/torch-int

  This repository contains integer operators on GPUs for PyTorch.

  Language:Python18722150

• snap-research/BitsFusion

  1272651

• ChenMnZ/PrefixQuant

  An algorithm for static activation quantization of LLMs

  Language:Python1015204

• Linwei-Chen/LIS

  IJCV2023 Instance Segmentation in the Dark

  Language:Python791207

• OswaldHe/HMT-pytorch

  Official Implementation of "HMT: Hierarchical Memory Transformer for Long Context Language Processing"

  Language:Python62232

• cauyxy/bilivideos

  Language:Jupyter Notebook52229

• ThisisBillhe/EfficientDM

  [ICLR 2024 Spotlight] This is the official PyTorch implementation of "EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models"

  Language:Jupyter Notebook513104

• thu-nics/ViDiT-Q

  ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation

  Language:Jupyter Notebook38165

• thu-nics/MixDQ

  [ECCV24] MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization

  Language:Python323144

• Kai-Liu001/2DQuant

  PyTorch code for our paper "2DQuant: Low-bit Post-Training Quantization for Image Super-Resolution"

  Language:Python19200

• 1hunters/retraining-free-quantization

  RFQuant: Retraining-free Model Quantization via One-Shot Weight-Coupling Learning, CVPR (2024)

  Language:Python8221

• zysxmu/ERQ

  Language:Python6101