Yan Qian's starred repositories
gpt_academic
为GPT/GLM等LLM大语言模型提供实用化交互接口,特别优化论文阅读/润色/写作体验,模块化设计,支持自定义快捷按钮&函数插件,支持Python和C++等项目剖析&自译解功能,PDF/LaTex论文翻译&总结功能,支持并行问询多种LLM模型,支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。
so-vits-svc
SoftVC VITS Singing Voice Conversion
deep-learning-for-image-processing
deep learning for image processing including classification and object-detection etc.
CVPR2024-Papers-with-Code
CVPR 2024 论文和开源项目合集
Awesome-Multimodal-Large-Language-Models
:sparkles::sparkles:Latest Advances on Multimodal Large Language Models
graph-based-deep-learning-literature
links to conference publications in graph-based deep learning
FedML
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
code-of-learn-deep-learning-with-pytorch
This is code of book "Learn Deep Learning with PyTorch"
Awesome-Domain-LLM
收集和梳理垂直领域的开源模型、数据集及评测基准。
Awesome-Federated-Learning
FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
Awesome-Federated-Machine-Learning
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
awesome-phd-advice
Collection of advice for prospective and current PhD students
wechat-windows-versions
保存微信历史版本
Awesome-FL
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
Federated-Learning-PyTorch
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
federated-learning
A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561
ChatPaper2Xmind
论文XMind笔记生成工具,将论文pdf通过ChatGPT转换为带有图片和公式的简要XMind笔记,提高论文阅读效率。
Federated-Learning-in-PyTorch
Handy PyTorch implementation of Federated Learning (for your painless research)