VTube Studio API Development Page

A recreation of Neuro-Sama originally created in 7 days.

Easy, fast, and cheap pretrain,finetune, serving for everyone

Makes your AI vtuber

AI Vtuber是一个由 【ChatterBot/ChatGPT/claude/langchain/chatglm/text-gen-webui/闻达/千问/kimi/ollama】 驱动的虚拟主播【Live2D/UE/xuniren】，可以在 【Bilibili/抖音/快手/微信视频号/拼多多/斗鱼/YouTube/twitch/TikTok】 直播中与观众实时互动 或 直接在本地进行聊…

Talk to any LLM with hands-free voice interaction, voice interruption, and Live2D taking face running locally across platforms

AI Vtuber for Streaming on Youtube/Twitch

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

"他山之石、可以攻玉"：复旦白泽智能发布面向国内开源和国外商用大模型的Demo数据集JADE-DB

Transform datasets at scale. Optimize datasets for fast AI model training.

Make PyTorch models up to 40% faster! Thunder is a source to source compiler for PyTorch. It enables using different hardware executors at once; across one or thousands of GPUs.

20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.

When it comes to optimizers, it's always better to be safe than sorry

Implementation of the proposed minGRU in Pytorch

Public repository for "The Surprising Effectiveness of Test-Time Training for Abstract Reasoning"

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

Offical implementation of "Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips" (ICLR2024)

Offical implementation of "Attention Spiking Neural Networks" (IEEE T-PAMI2023)

maximal update parametrization (µP)

Official Implementation of TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters

"LightRAG: Simple and Fast Retrieval-Augmented Generation"

Agent S: an open agentic framework that uses computers like a human

Get your documents ready for gen AI

End-to-End Autonomous Driving with Spiking Neural Networks

State Space Models

Non official implementation of the Linear Recurrent Unit (LRU, Orvieto et al. 2023)

Understand and test language model architectures on synthetic tasks.

Collection of papers on state-space models