Reinforcement Learning
stable-baselines3
PandaReachDense-v3
a2c
panda-gym
deep-rl-class
Eval Results (legacy)
Instructions to use jnforja/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use jnforja/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="jnforja/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
File size: 382 Bytes
a7f14ef | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"env_id": "PandaReachDense-v3",
"repo_id": "jnforja/a2c-PandaReachDense-v3",
"model_name": "a2c-PandaReachDense-v3",
"seed": 42,
"n_envs": 4,
"total_timesteps": 1000000,
"policy": "MultiInputPolicy",
"model_architecture": "A2C",
"norm_obs": true,
"norm_reward": true,
"clip_obs": 10.0,
"eval_episodes": 10,
"video_episodes": 1,
"min_video_seconds": 3
} |