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Stable Diffusion web UI
Models and examples built with TensorFlow
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, m…
scikit-learn: machine learning in Python
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
基于大模型搭建的聊天机器人，同时支持 微信公众号、企业微信应用、飞书、钉钉 等接入，可选择GPT3.5/GPT-4o/GPT4.0/ Claude/文心一言/讯飞星火/通义千问/ Gemini/GLM-4/Claude/Kimi/LinkAI，能处理文本、语音和图片，访问操作系统和互联网，支持基于自有知识库进行定制企业智能客服。
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Code for the paper "Language Models are Unsupervised Multitask Learners"
Use ChatGPT to summarize the arXiv papers. 全流程加速科研，利用chatgpt进行论文全文总结+专业翻译+润色+审稿+审稿回复
PyTorch implementations of Generative Adversarial Networks.
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
code for Data Science From Scratch book
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
Official Tensorflow implementation of U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation (ICLR 2020)
An Industrial Grade Federated Learning Framework
Web interface for browsing, search and filtering recent arxiv submissions
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 o…
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
PyTorch original implementation of Cross-lingual Language Model Pretraining.
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf
A library of sklearn compatible categorical variable encoders