Results for “environments”
5 skills
k-dense-ai stable-baselines3
Train reinforcement learning agents using PPO, SAC, DQN, TD3, DDPG, and A2C algorithms with a scikit-learn-like API. Supports custom Gymnasium environments, vectorized environments, callbacks, and model persistence.
30.2k · bundle
k-dense-ai pufferlib
Train reinforcement learning agents at millions of steps per second using optimized PPO, vectorized environments, and multi-agent support.
30.2k · bundle
More results
google agent-platform-tuning
Fine-tune open models or Gemini models using Agent Platform infrastructure, from environment setup through data preparation, job configuration, monitoring, and deployment.
14.4k · bundle
mukul975 detecting-anomalies-in-industrial-control-systems
Deploys anomaly detection for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications.
24.6k · bundle
orchestra-research fine-tuning-serving-openpi
Fine-tune and serve Physical Intelligence OpenPI models (pi0, pi0-fast, pi0.5) using JAX or PyTorch backends for robot policy inference across ALOHA, DROID, and LIBERO environments.
10.4k · bundle