Beast code in Giters

sarhaan's starred repositories

meilisearch

A lightning-fast search API that fits effortlessly into your apps, websites, and workflow

Language:RustMIT46298 286 1947

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 NotebookApache-2.010332 64 214

mujoco

Multi-Joint dynamics with Contact. A general purpose physics simulator.

Language:Jupyter NotebookApache-2.07777 103 1452

o3de

Open 3D Engine (O3DE) is an Apache 2.0-licensed multi-platform 3D engine that enables developers and content creators to build AAA games, cinema-quality 3D worlds, and high-fidelity simulations without any fees or commercial obligations.

Language:C++NOASSERTION7633 143 7505

Delta

Delta is an all-in-one classic video game emulator for non-jailbroken iOS devices.

Language:Swift4796 103 387

fasthtml

The fastest way to create an HTML app

Language:Jupyter NotebookApache-2.04775 40 228

RouteLLM

A framework for serving and evaluating LLM routers - save LLM costs without compromising quality!

Language:PythonApache-2.02836 24 43

chameleon

Repository for Meta Chameleon, a mixed-modal early-fusion foundation model from FAIR.

Language:PythonNOASSERTION1737 25 46

Low-Cost-Mocap

Low cost motion capture system for room scale tracking

Language:TypeScriptMIT1481 35 27

mujoco_menagerie

A collection of high-quality models for the MuJoCo physics engine, curated by Google DeepMind.

Language:Jupyter NotebookNOASSERTION1249 25 65

openvla

OpenVLA: An open-source vision-language-action model for robotic manipulation.

Language:PythonMIT926 16 67

octo

Octo is a transformer-based robot policy trained on a diverse mix of 800k robot trajectories.

Language:PythonMIT750 19 92

TeleVision

Open-TeleVision: Teleoperation with Immersive Active Visual Feedback

Language:PythonNOASSERTION552 7 29

MuJoCo_RL_UR5

A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.

Language:PythonMIT405 4 25