artemZholus

artemZholus's Stars

• xai-org/grok-1

  Grok open release

  Language:Python49.8k5912148.3k

• vllm-project/vllm

  A high-throughput and memory-efficient inference and serving engine for LLMs

  Language:Python32.7k2715.7k5k

• feder-cr/linkedIn_auto_jobs_applier_with_AI

  LinkedIn_AIHawk is a tool that automates the jobs application process on LinkedIn. Utilizing artificial intelligence, it enables users to apply for multiple job offers in an automated and personalized way.

  Language:Python12.6k822632k

• shadps4-emu/shadPS4

  PS4 emulator for Windows,Linux,MacOS

  Language:C++12.1k133674809

• facebookresearch/segment-anything-2

  The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

  Language:Jupyter Notebook11.1k64259944

• nerfies/nerfies.github.io

  Language:JavaScript2.7k385992

• eloialonso/diamond

  DIAMOND (DIffusion As a Model Of eNvironment Dreams) is a reinforcement learning agent trained in a diffusion world model. NeurIPS 2024 Spotlight.

  Language:Python1.7k2036111

• n2cholas/awesome-jax

  JAX - A curated list of resources https://github.com/google/jax

  1.6k518134

• lichao-sun/Mora

  Mora: More like Sora for Generalist Video Generation

  Language:Python1.5k8111100

• NVIDIA/nccl-tests

  NCCL Tests

  Language:Cuda94826238251

• ccsb-scripps/AutoDock-GPU

  AutoDock for GPUs and other accelerators

  Language:C++41915210114

• proroklab/VectorizedMultiAgentSimulator

  VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

  Language:Python35996072

• google/grain

  Library for reading and processing ML training data.

  Language:Python344112126

• shacklettbp/madrona

  Language:C++32991232

• MichaelTMatthews/Craftax

  (Crafter + NetHack) in JAX. ICML 2024 Spotlight.

  Language:Python22231422

• soniajoseph/ViT-Prisma

  ViT Prisma is a mechanistic interpretability library for Vision Transformers (ViTs).

  Language:Jupyter Notebook19096119

• keraJLi/rejax

  Language:Python1594107

• jurgisp/memory-maze

  Evaluating long-term memory of reinforcement learning algorithms

  Language:Python13633014

• mttga/purejaxql

  Simple single-file baselines for Q-Learning in pure-GPU setting

  Language:Python130108

• allenai/discoveryworld

  A virtual environment for developing and evaluating automated scientific discovery agents.

  Language:Python110828

• MichalBortkiewicz/JaxGCRL

  Goal-Conditioned Reinforcement Learning with JAX

  Language:Jupyter Notebook1072513

• nshepperd/flash_attn_jax

  JAX bindings for Flash Attention v2

  Language:C++82473

• weipu-zhang/STORM

  Language:Python692612

• DramaCow/jaxued

  Language:Python66208

• JoeyTeng/jaxrenderer

  Differentiable Rasteriser implemented in JAX. Reference: https://github.com/erwincoumans/tinyrenderer, https://github.com/ssloy/tinyrenderer/wiki; PR: https://github.com/google/brax/pull/367

  Language:Jupyter Notebook66457

• chandar-lab/Recall2Imagine

  Recall to Imagine, a model-based RL algorithm with superhuman memory. Oral (1.2%) @ ICLR 2024

  Language:Python577115

• Cognitive-AI-Systems/learn-to-follow

  [AAAI-2024] Follower: This study addresses the challenging problem of decentralized lifelong multi-agent pathfinding. The proposed Follower approach utilizes a combination of a planning algorithm for constructing a long-term plan and reinforcement learning for resolving local conflicts.

  Language:C++37322

• johnryan465/pscan

  Language:Python36113

• Cognitive-AI-Systems/IGOR

  Language:Python161

• lebrice/torch_jax_interop

  Simple tools to mix and match PyTorch and Jax - Get the best of both worlds!

  Language:Python16201