Popular GitHub Repositories for Space Exploration

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.

CSGHub is a brand-new open-source platform for managing LLMs, developed by the OpenCSG team. It offers both open-source and on-premise/SaaS solutions, with features comparable to Hugging Face. Gain full control over the lifecycle of LLMs, datasets, and agents, with Python SDK compatibility with Hugging Face. Join us! ??

MuseTalk: Real-Time High Quality Lip Synchorization with Latent Space Inpainting

A distributed approximate nearest neighborhood search (ANN) library which provides a high quality vector index build, search and distributed online serving toolkits for large scale vector search scenario.

Create ? videos with Stable Diffusion by exploring the latent space and morphing between text prompts

MS-Agent: Lightweight Framework for Empowering Agents with Autonomous Exploration

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

Minkowski Engine is an auto-diff neural network library for high-dimensional sparse tensors

Large Concept Models: Language modeling in a sentence representation space

Use supervised learning to illuminate the latent space of GAN for controlled generation and edit

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

For deep RL and the future of AI.

[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning

DataFrames for Go: For statistics, machine-learning, and data manipulation/exploration

Automatically find issues in image datasets and practice data-centric computer vision.

GELab: GUI Exploration Lab. One of the best GUI agent solutions in the galaxy, built by the StepFun-GELab team and powered by Step’s research capabilities.

AIDE: AI-Driven Exploration in the Space of Code. State of the Art machine Learning engineering agents that automates AI R&D.

A 2D space exploration and mining game made with Godot and our AI framework

Code implementation of "Learning Efficient Online 3D Bin Packing on Packing Configuration Trees". We propose to enhance the practical applicability of online 3D Bin Packing Problem (BPP) via learning on a hierarchical packing configuration tree which makes the deep reinforcement learning (DRL) model easy to deal with practical constraints and well-performing even with continuous solution space.