Reinforcement Learning
stable-baselines3
PandaPickAndPlace-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use hishamcse/a2c-PandaPickAndPlace-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use hishamcse/a2c-PandaPickAndPlace-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="hishamcse/a2c-PandaPickAndPlace-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
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Download README.md from hishamcse/a2c-PandaPickAndPlace-v3: direct link, hf CLI and curl.
- Browser
- Download file 1.28 kB
-
https://huggingface.co/hishamcse/a2c-PandaPickAndPlace-v3/resolve/main/README.md
- Command line
-
hf download hf://hishamcse/a2c-PandaPickAndPlace-v3/README.md
-
curl -L -o README.md https://huggingface.co/hishamcse/a2c-PandaPickAndPlace-v3/resolve/main/README.md
1.28 kB
metadata
library_name: stable-baselines3
tags:
- PandaPickAndPlace-v3
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: A2C
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: PandaPickAndPlace-v3
type: PandaPickAndPlace-v3
metrics:
- type: mean_reward
value: '-50.00 +/- 0.00'
name: mean_reward
verified: false
A2C Agent playing PandaPickAndPlace-v3
This is a trained model of a A2C agent playing PandaPickAndPlace-v3 using the stable-baselines3 library. To see full code, visit: https://www.kaggle.com/code/syedjarullahhisham/drl-huggingface-unit-6-pandagym-reachdns-pickplace
Codes
Github repos(Give a star if found useful):
- https://github.com/hishamcse/DRL-Renegades-Game-Bots
- https://github.com/hishamcse/Advanced-DRL-Renegades-Game-Bots
- https://github.com/hishamcse/Robo-Chess
Kaggle Notebook:
Usage (with Stable-baselines3)
TODO: Add your code
from stable_baselines3 import ...
from huggingface_sb3 import load_from_hub
...