warp-drive
chainer
| warp-drive | chainer | |
|---|---|---|
| 1 | 2 | |
| 435 | 5,867 | |
| 1.1% | 0.1% | |
| 8.1 | 0.0 | |
| 26 days ago | 9 months ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
warp-drive
-
[N] Salesforce Open-Sources ‘WarpDrive’, A Light Weight Reinforcement Learning (RL) Framework That Implements End-To-End Multi-Agent RL On A Single GPU
4 Min Read | Codes | Paper | SalesForce Blog
chainer
-
ChaiNNer – Node/Graph based image processing and AI upscaling GUI
There is already an AI framework named Chainer: https://github.com/chainer/chainer
-
Protip: the upscaler matters a lot
Sorry maybe someone could chime in and help but I use chainer to upscale. https://github.com/chainer/chainer
What are some alternatives?
Simple-MADRL-Chess - MADRL project solving chess environment using PPO with two different methods: 2 agents/networks and a single agent/network.
chaiNNer - A node-based image processing GUI aimed at making chaining image processing tasks easy and customizable. Born as an AI upscaling application, chaiNNer has grown into an extremely flexible and powerful programmatic image processing application.
TransformerEngine - A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.
leptonai - A Pythonic framework to simplify AI service building
simba-ps - Fast deterministic all-Python Lennard-Jones particle simulator that utilizes Numba for GPU-accelerated computation.
tmu - Implements the Tsetlin Machine, Coalesced Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features, drop clause, Type III Feedback, focused negative sampling, multi-task classifier, autoencoder, literal budget, and one-vs-one multi-class classifier. TMU is written in Python with wrappers for C and CUDA-based clause evaluation and updating.
torchrec - Pytorch domain library for recommendation systems
XNOR-popcount-GEMM-PyTorch-CPU-CUDA - A PyTorch implemenation of real XNOR-popcount (1-bit op) GEMM Linear PyTorch extension support both CPU and CUDA
jittor - Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
SmallPebble - Minimal deep learning library written from scratch in Python, using NumPy/CuPy.
cog - Containers for machine learning
pytortto - deep learning from scratch. uses numpy/cupy, trains in GPU, follows pytorch API