George Ang (gnap)

gnap

User data from Github https://github.com/gnap

Company:zhihu.com

Location:Beijing

GitHub:@gnap

George Ang's repositories

EAGLE

Official Implementation of EAGLE-1 and EAGLE-2

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alertmanager

Prometheus Alertmanager

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AudioModem

Transfer data using microphone/speaker on iOS devices

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bagua

Bagua Speeds up PyTorch

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BMTrain

Efficient Training (including pre-training and fine-tuning) for Big Models

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ColossalAI

Colossal-AI: A Unified Deep Learning System for Big Model Era

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CommunicationDebugger

Network communication debugger iOS app Swift source code

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EpicSurvivalGame

Third-person Survival Game for Unreal Engine 4 (Sample Project)

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go-sendcloud

SendCloud mail API client in Go

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cutlass

CUDA Templates for Linear Algebra Subroutines

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flash-attention

Fast and memory-efficient exact attention

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go-tcp-proxy

A small TCP proxy written in Go

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mars

Mars is a cross-platform network component developed by WeChat.

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ModelCenter

Efficient, Low-Resource, Distributed transformer implementation based on BMTrain

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mtr

Golang native MTR implementation

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neovim

Vim-fork focused on extensibility and agility.

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NOTTaskPaperForIOS

Source code for the original TaskPaper for iOS.

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prezto

The configuration framework for Zsh

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pygit2

Python bindings for libgit2

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pytorch-gpu-benchmark

Using the famous cnn model in Pytorch, we run benchmarks on various gpu.

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scope

职业信息文档

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socket.IO-objc

socket.io v0.7.2+ for iOS devices

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stream-lua-nginx-module

Embed the power of Lua into NGINX TCP/UDP servers

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supervisor

Supervisor process control system for UNIX

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tensorflow

An Open Source Machine Learning Framework for Everyone

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TensorFlow-Examples

TensorFlow Tutorial and Examples for Beginners with Latest APIs

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TLLM_QMM

TLLM_QMM strips the implementation of quantized kernels of Nvidia's TensorRT-LLM, removing NVInfer dependency and exposes ease of use Pytorch module. We modified the dequantation and weight preprocessing to align with popular quantization alogirthms such as AWQ and GPTQ, and combine them with new FP8 quantization.

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transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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vllm

A high-throughput and memory-efficient inference and serving engine for LLMs

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ZhiLight

A highly optimized LLM inference acceleration engine for Llama and its variants.

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