Popular GitHub Repositories for Graph Attention Autoencoder

??? 60+ Implementations/tutorials of deep learning papers with side-by-side notes ?; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ? reinforcement learning (ppo, dqn), capsnet, distillation, ... ?

Cross-platform, customizable ML solutions for live and streaming media.

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Graph Neural Network Library for PyTorch

Make interlinked notes in private (E2E encrypted), share parts of it to global network of topics with deep AI integration

Machine learning, in numpy

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

Natural Language Processing Tutorial for Deep Learning Researchers

RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.

Python package built to ease deep learning on graph, on top of existing DL frameworks.

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

Reliable LLM Memory for AI Applications and AI Agents

A Python Library for Outlier and Anomaly Detection, Integrating Classical and Deep Learning Techniques

A PyTorch implementation of the Transformer model in "Attention is All You Need".

Anomaly detection related books, papers, videos, and toolboxes

Implementation of RLHF (Reinforcement Learning with Human Feedback) on top of the PaLM architecture. Basically ChatGPT but with PaLM

BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)

VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech

FlowGram是一个基于节点的流程构建引擎，帮助开发者快速创建工作流程，支持固定布局和自由连接布局两种模式。

中文LLaMA-2 & Alpaca-2大模型二期项目 + 64K超长上下文模型 (Chinese LLaMA-2 & Alpaca-2 LLMs with 64K long context models)