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auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

awesome-chatgpt-prompts

This repo includes ChatGPT prompt curation to use ChatGPT better.

awesome-chatgpt-prompts-zh

ChatGPT 中文调教指南。各种场景使用指南。学习怎么让它听你的话。

bert-pytorch

Google AI 2018 BERT pytorch implementation

chatgpt

Reverse engineered ChatGPT API

chatgpt-1

🔮 ChatGPT Desktop Application (Mac, Windows and Linux)

chatgpt-alternative

You.com ChatGPT Clone client - Google on steroids

chatgpt-clone

ChatGPT interface with better UI

chatgpt-web

用 Express 和 Vue3 搭建的 ChatGPT 演示网页

code1

ddos-ml-detection

Detects DDOS attacks using ML

ddos_traffic_classification

Identifying malicious/benign network traffic using classification methods.

fast-stable-diffusion

fast-stable-diffusion + DreamBooth

few-shot

Repository for few-shot learning machine learning projects

glide-text2im

GLIDE: a diffusion-based text-conditional image synthesis model

gnidart

gpt4free

decentralising the Ai Industry, just some language model api's...

hands-on-deep-learning-for-iot

Hands-On Deep Learning for IoT, published by Packt

hello-algo

《Hello 算法》：动画图解、一键运行的数据结构与算法教程，支持 Java, C++, Python, Go, JS, TS, C#, Swift, Rust, Dart, Zig 等语言。

iot-cyber-security-with-machine-learning-research-project

IoT networks have become an increasingly valuable target of malicious attacks due to the increased amount of valuable user data they contain. In response, network intrusion detection systems have been developed to detect suspicious network activity. UNSW-NB15 is an IoT-based network traffic data set with different categories for normal activities and malicious attack behaviors. UNSW-NB15 botnet datasets with IoT sensors' data are used to obtain results that show that the proposed features have the potential characteristics of identifying and classifying normal and malicious activity. Role of ML algorithms is for developing a network forensic system based on network flow identifiers and features that can track suspicious activities of botnets is possible. The ML model metrics using the UNSW-NB15 dataset revealed that ML techniques with flow identifiers can effectively and efficiently detect botnets’ attacks and their tracks.

iot-security-2

To provide security from DoS and DDoS attacks, various solutions have been proposed. In this project, Machine Learning, as well as Deep Learning algorithms, have been employed to analyze the DoS and DDoS attacks.

iotsecuritywithdeeplearning

Exploration of methods for IoT Device Security with MUD and Deep LEarning

leedl-tutorial

《李宏毅深度学习教程》，PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

lit-llama

Implementation of the LLaMA language model based on nanoGPT. Supports flash attention, Int8 and GPTQ 4bit quantization, LoRA and LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed.

nanogpt

The simplest, fastest repository for training/finetuning medium-sized GPTs.

paper-reading

深度学习经典、新论文逐段精读

project

DDoS attacks detection by using SVM on SDN networks.

segment-any-anomaly

Official implementation of "Segment Any Anomaly without Training via Hybrid Prompt Regularization (SAA+)".

spatialattentiongan

SaGAN PyTorch "Generative Adversarial Network with Spatial Attention for Face Attribute Editing"

stable-diffusion

A latent text-to-image diffusion model