wandb
stable-baselines3
wandb | stable-baselines3 | |
---|---|---|
16 | 46 | |
8,211 | 7,953 | |
1.6% | 3.1% | |
9.9 | 8.2 | |
5 days ago | 5 days ago | |
Python | Python | |
MIT 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.
wandb
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A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
Weights & Biases — The developer-first MLOps platform. Build better models faster with experiment tracking, dataset versioning, and model management. Free tier for personal projects only, with 100 GB of storage included.
- Northlight makes Alan Wake 2 shine
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The last sentence of Lowes conveniently missing from OpenAI...
HuggingFace and wandb.ai (both competitors of OpenAI) both also have "do own research"
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Efficient way to tune a network by changing hyperparameters?
Wandb is the best! https://wandb.ai/
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[D] Monitoring production image models
To track stuff I've used wandb.ai in a company in the past, as someone else pointed out. Regarding metrics... This is really specific to your domain, and it is such a broad question. You could count color pixels, the distribution of intensity histograms, etc etc.
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How to use the colab notebook version of Dall-E mini and bypass the traffic limit - A guide
Step 1: The colab notebook uses wandb.ai, so you need to register for a wandb.ai account beforehand if you want to use the colab notebook. After registering you need to go to your homepage and copy the API key and paste/keep it somewhere.
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Roadmap for learning MLOps (for DevOps engineers)
I want to take a look at tools like https://wandb.ai/ and they would integrate into some of the pipelines I'm playing with.
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What's a sequel that got you thinking "the people who made this COMPLETELY missed the point of the first one"?
does current cgi and ai tech can bring back leslie nielsen? might use unreal engine and https://www.resemble.ai/ or https://wandb.ai/?
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What MLOps tools and processes do you use?
I'm currently working for a MLOps company so I'm heavily using their tools (Weights & Biases) but I've used custom C++ for deployment, Pytorch + fastai for quick experimentation, Weights & Biases for experiment tracking, hyper-parameter tuning + model versioning (hence why I went to work for them), custom database + data pipeline, HoloViz for data visualisation (really nice dashboarding tool), Jenkins for CI/CD, I also love Github Actions.
- [D] Best resources or tools to draw nicer table for comparing different models/frameworks performance
stable-baselines3
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Sim-to-real RL pipeline for open-source wheeled bipeds
The latest release (v3.0.0) of Upkie's software brings a functional sim-to-real reinforcement learning pipeline based on Stable Baselines3, with standard sim-to-real tricks. The pipeline trains on the Gymnasium environments distributed in upkie.envs (setup: pip install upkie) and is implemented in the PPO balancer. Here is a policy running on an Upkie:
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[P] PettingZoo 1.24.0 has been released (including Stable-Baselines3 tutorials)
PettingZoo 1.24.0 is now live! This release includes Python 3.11 support, updated Chess and Hanabi environment versions, and many bugfixes, documentation updates and testing expansions. We are also very excited to announce 3 tutorials using Stable-Baselines3, and a full training script using CleanRL with TensorBoard and WandB.
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[Question] Why there is so few algorithms implemented in SB3?
I am wondering why there is so few algorithms in Stable Baselines 3 (SB3, https://github.com/DLR-RM/stable-baselines3/tree/master)? I was expecting some algorithms like ICM, HIRO, DIAYN, ... Why there is no model-based, skill-chaining, hierarchical-RL, ... algorithms implemented there?
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Stable baselines! Where my people at?
Discord is more focused, and they have a page for people who wants to contribute https://github.com/DLR-RM/stable-baselines3/blob/master/CONTRIBUTING.md
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SB3 - NotImplementedError: Box([-1. -1. -8.], [1. 1. 8.], (3,), <class 'numpy.float32'>) observation space is not supported
Therefore, I debugged this error to the ReplayBuffer that was imported from `SB3`. This is the problem function -
- Exporting an A2C model created with stable-baselines3 to PyTorch
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Shimmy 1.0: Gymnasium & PettingZoo bindings for popular external RL environments
Have you ever wanted to use dm-control with stable-baselines3? Within Reinforcement learning (RL), a number of APIs are used to implement environments, with limited ability to convert between them. This makes training agents across different APIs highly difficult, and has resulted in a fractured ecosystem.
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Stable-Baselines3 v1.8 Release
Changelog: https://github.com/DLR-RM/stable-baselines3/releases/tag/v1.8.0
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[P] Reinforcement learning evolutionary hyperparameter optimization - 10x speed up
Great project! One question though, is there any reason why you are not using existing RL models instead of creating your own, such as stable baselines?
- Is stable-baselines3 compatible with gymnasium/gymnasium-robotics?
What are some alternatives?
tensorboard - TensorFlow's Visualization Toolkit
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
guildai - Experiment tracking, ML developer tools
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
pytorch-summary - Model summary in PyTorch similar to `model.summary()` in Keras
cleanrl - High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
tianshou - An elegant PyTorch deep reinforcement learning library.
Tetris-deep-Q-learning-pytorch - Deep Q-learning for playing tetris game
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros