Popular GitHub Repositories for Instruction Set Architecture

Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.

[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

:sparkles::sparkles:Latest Advances on Multimodal Large Language Models

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

The official GitHub page for the survey paper "A Survey of Large Language Models".

AutoML library for deep learning

An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

BELLE: Be Everyone's Large Language model Engine（开源中文对话大模型）

An open source implementation of Microsoft's VALL-E X zero-shot TTS model. Demo is available in https://plachtaa.github.io/vallex/

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

A Collection of Variational Autoencoders (VAE) in PyTorch.

Venom is a high-performance system developed with JavaScript to create a bot for WhatsApp, support for creating any interaction, such as customer service, media sending, sentence recognition based on artificial intelligence and all types of design architecture for WhatsApp.

Reliable LLM Memory for AI Applications and AI Agents

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

AirLLM 70B inference with single 4GB GPU

Publication-ready NN-architecture schematics.

A concise but complete full-attention transformer with a set of promising experimental features from various papers