Ryan Dai's Projects
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Keras implementation of Deep Convolutional Generative Adversarial Networks
带你从零实现一个高性能的深度学习推理库,支持Unet、Yolov5、Resnet等模型的推理。Implement a high-performance deep learning inference library step by step
Leveraging Large Language Models for Visual Target Navigation
LangServe 🦜️🏓
Spring+SpringMVC+MyBatis+Bootstrap+Vue开发在线学习系统
Lecture Slides for Philip Levis and Nick McKeown's "Introduction to Computer Networking" Stanford course
😏 LeetCode solutions in any programming language | 多种编程语言实现 LeetCode、《剑指 Offer(第 2 版)》、《程序员面试金典(第 6 版)》题解
《代码随想录》LeetCode 刷题攻略:200道经典题目刷题顺序,共60w字的详细图解,视频难点剖析,50余张思维导图,支持C++,Java,Python,Go,JavaScript等多语言版本,从此算法学习不再迷茫!🔥🔥 来看看,你会发现相见恨晚!🚀
Demonstrate all the questions on LeetCode in the form of animation.(用动画的形式呈现解LeetCode题目的思路)
Self-calculated rating of problems in leetcode weekly/biweekly contests.
Official code release for "Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning"
Code for LGX (Language Guided Exploration). We use LLMs to perform embodied robot navigation in a zero-shot manner.
🛠 A lite C++ toolkit of awesome AI models with ONNXRuntime, NCNN, MNN and TNN. YOLOv5, YOLOX, YOLOP, YOLOv6, YOLOR, MODNet, YOLOX, YOLOv7, YOLOv8. MNN, NCNN, TNN, ONNXRuntime.
Fine-tuning LLaMA to follow Instructions within 1 Hour and 1.2M Parameters
Easy-to-use LLM fine-tuning framework (LLaMA, BLOOM, Mistral, Baichuan, Qwen, ChatGLM)
An Open-source Toolkit for LLM Development
本项目旨在分享大模型相关技术原理以及实战经验。
The paper list of the 86-page paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.
Long Range Arena for Benchmarking Efficient Transformers
AI Research Platform for Reinforcement Learning from Real Panoramic Images.
Welcome to NEUP Net Department!
这是一个来源于字节跳动后端青训营的项目。A project from ByteDance backend youth training camp.
4 labs + 2 challenges + 4 docs
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现,也是作为一个算法工程师必会的理论基础知识。