Pinned Repositories
Awesome-Developer-Resource
이 레포지토리는 저의 관심사 그리고 유용한 개발 정보를 수록해놓았습니다.
Convolutions-to-Vision-Transformers
[Not Official] Implementation of CvT, Convolutions to Vision Transformers
Deep-Complex-Networks
[Not Official] Implementation Deep Comple Networks and Plug-in module (e.g. Neural Preprocessing Layer, ICLR 2018)
Digging-into-Self-Supervised-Monocular-Depth-Estimation
[Not Official] Implementation of monodepth2, ICCV 2019
Generative-Adversarial-Network-Tutorial
Implementation GAN for MNIST, Simpson, Pokemon
NeRF-Representing-Scenes-as-Neural-Radiance-Fields-for-View-Synthesis
[Not Official] Simple NeRF training pipeline, ECCV 2020
Neural-Network-Pruning-Tutorial
Tutorial impelmentation of Neural Network Pruning for VGG
Phase-aware-Deep-Complex-UNet
[Not Official] Implementation DC-UNet, ICLR 2019
Self-Supervised-Monocular-Sceneflow-Estimation
[Not Official] Implementation of monocular sceneflow estimation, CVPR 2020
Temporal-Convolution-Resnet
[Not Official] Implementation of TC-Resnet, INTERSPEECH 2019
russellgeum's Repositories
russellgeum/Deep-Complex-Networks
[Not Official] Implementation Deep Comple Networks and Plug-in module (e.g. Neural Preprocessing Layer, ICLR 2018)
russellgeum/Phase-aware-Deep-Complex-UNet
[Not Official] Implementation DC-UNet, ICLR 2019
russellgeum/Temporal-Convolution-Resnet
[Not Official] Implementation of TC-Resnet, INTERSPEECH 2019
russellgeum/Convolutions-to-Vision-Transformers
[Not Official] Implementation of CvT, Convolutions to Vision Transformers
russellgeum/Digging-into-Self-Supervised-Monocular-Depth-Estimation
[Not Official] Implementation of monodepth2, ICCV 2019
russellgeum/Generative-Adversarial-Network-Tutorial
Implementation GAN for MNIST, Simpson, Pokemon
russellgeum/NeRF-Representing-Scenes-as-Neural-Radiance-Fields-for-View-Synthesis
[Not Official] Simple NeRF training pipeline, ECCV 2020
russellgeum/Neural-Network-Pruning-Tutorial
Tutorial impelmentation of Neural Network Pruning for VGG
russellgeum/Awesome-Developer-Resource
이 레포지토리는 저의 관심사 그리고 유용한 개발 정보를 수록해놓았습니다.
russellgeum/Microsoft-Phi-3-CookBook
This is a Phi-3 book for getting started with Phi-3. Phi-3, a family of open AI models developed by Microsoft. Phi-3 models are the most capable and cost-effective small language models (SLMs) available, outperforming models of the same size and next size up across a variety of language, reasoning, coding, and math benchmarks.
russellgeum/AutoAWQ
AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference. Documentation:
russellgeum/LLM-Finetuning-Tutorial
This repository is LLM finetuning tutorial using Gemma-2B
russellgeum/SLM-Pruning-Quantization
Pruning, Quantization recipe for Small Language Model
russellgeum/Stand-Alone-Self-Attention
[Not Official] Implementation of Stand-Alone-Self-Attention, NeurIPS 2019
russellgeum/Self-Supervised-Monocular-Sceneflow-Estimation
[Not Official] Implementation of monocular sceneflow estimation, CVPR 2020
russellgeum/Apache-TVM
Open deep learning compiler stack for cpu, gpu and specialized accelerators
russellgeum/Apple-MLX
MLX: An array framework for Apple silicon
russellgeum/AutoGPTQ
An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.
russellgeum/ComputeLibrary
The Compute Library is a set of computer vision and machine learning functions optimised for both Arm CPUs and GPUs using SIMD technologies.
russellgeum/llama.cpp
Port of Facebook's LLaMA model in C/C++
russellgeum/mlc-llm
Universal LLM Deployment Engine with ML Compilation
russellgeum/Programming-Solver
russellgeum/Pseudolab-nnLabmlai
nnLabmlai 한글화 작업
russellgeum/russellgeum
Profile
russellgeum/russellgeum.github.io
russellgeum/Speech-Preprocessing
Speech Data Preprocessing Tool for Deep Learning
russellgeum/TensorRT-LLM
TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.
russellgeum/VideoDataset
비디오 데이터셋 핸들링 및 튜토리얼
russellgeum/vllm
A high-throughput and memory-efficient inference and serving engine for LLMs