lakehui's Stars
meta-llama/llama-recipes
Scripts for fine-tuning Meta Llama with composable FSDP & PEFT methods to cover single/multi-node GPUs. Supports default & custom datasets for applications such as summarization and Q&A. Supporting a number of candid inference solutions such as HF TGI, VLLM for local or cloud deployment. Demo apps to showcase Meta Llama for WhatsApp & Messenger.
facebookresearch/UmeTrack
UmeTrack Unified multi-view end-to-end hand tracking for VR
chengzhengxin/deep-sdm
deep-sdm is appied for face landmark.
onnx/onnx
Open standard for machine learning interoperability
fanglinpu/JGR-P2O
Tencent/TNN
TNN: developed by Tencent Youtu Lab and Guangying Lab, a uniform deep learning inference framework for mobile、desktop and server. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework.
Star-Clouds/CenterFace
face detection
switchablenorms/DeepFashion2
DeepFashion2 Dataset https://arxiv.org/pdf/1901.07973.pdf
ruanyf/document-style-guide
中文技术文档的写作规范
royeo/awesome-programming-books
📚 经典技术书籍推荐,持续更新...
HRNet/HRNet-Facial-Landmark-Detection
This is an official implementation of facial landmark detection for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919
ChriswooTalent/COCO_forYOLO
Extract training data set suitable for YOLO darknet from COCO database
apache/tvm
Open deep learning compiler stack for cpu, gpu and specialized accelerators
microsoft/MMdnn
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
jihunchoi/lsoftmax-pytorch
PyTorch implementation Large-Margin Softmax (L-Softmax) loss
lanpa/tensorboardX
tensorboard for pytorch (and chainer, mxnet, numpy, ...)
darkonhub/darkon
Toolkit to Hack Your Deep Learning Models
wentianli/knowledge_distillation_caffe
KnowledgeDistillation Layer (Caffe implementation)
naturomics/CapsNet-Tensorflow
A Tensorflow implementation of CapsNet(Capsules Net) in paper Dynamic Routing Between Capsules
HolmesShuan/ResNet-18-Caffemodel-on-ImageNet
ResNet-18 Caffemodel @ilsvrc12 shrt 256 with Top-1 69% Top-5 89%
seetaface/SeetaFaceEngine
oxford-cs-deepnlp-2017/lectures
Oxford Deep NLP 2017 course
lakehui/DeepID2_based_Inception
this network is built based on Inception. and optimize it by using identification loss and verification loss which derive from DeepID2+
BVLC/caffe
Caffe: a fast open framework for deep learning.
lakehui/Repeat-Buyers-Prediction
a project to predict the probability of repeated buyer
lakehui/matconvnet_caffe_convert
the project convert a matconvnet model to caffe model