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apollo

An open autonomous driving platform

bashrc

code-samples

Source code examples from the Parallel Forall Blog

code-server

VS Code in the browser

cup

CUP, common useful python-lib. (Currently, Most popular python lib in baidu)

docker-headless-vnc-container

Collection of Docker images with headless VNC environments

env-setup

env_setup

markdown-resume

⭐️ Markdown 简历模版

mars

Mars is a tensor-based unified framework for large-scale data computation.

muduo

A C++ non-blocking network library for multi-threaded server in Linux

nbdev-template

ncnn

ncnn is a high-performance neural network inference framework optimized for the mobile platform

olive

OLive, meaning ONNX go live, integrates model conversion, optimization, correctness test and performance tuning into a single pipeline and outputs a production ready ONNX model with ONNX Runtime configurations (execution provider + optimization options)

onnx

Open standard for machine learning interoperability

onnx-code-snippet

onnxruntime

ONNX Runtime

optimum

🏎️ Accelerate training and inference of 🤗 Transformers with easy to use hardware optimization tools

perf-tools

Performance analysis tools based on Linux perf_events (aka perf) and ftrace

rocm_documentation

ROCm Software Platform Documentation

sshfs-win

SSHFS For Windows

tensorflow-onnx

Convert TensorFlow models to ONNX

test-learning

test_azure_pipeline

the-art-of-command-line

Master the command line, in one page

timemory

Modular C++ Toolkit for Performance Analysis and Logging. Profiling API and Tools for C, C++, CUDA, Fortran, and Python. The C++ template API is essentially a framework to creating tools: it is designed to provide a unifying interface for recording various performance measurements alongside data logging and interfaces to other tools.

tldr

:books: Simplified and community-driven man pages

transformers

🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.

tutorials

Tutorials for using ONNX

vespa

Vespa is an engine for low-latency computation over large data sets.