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ppo-Huggy – AI Model by asiful2 | AlphaNeural AI | AlphaNeural AI
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asiful2
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ppo-Huggy
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ml-agents
tensorboard
onnx
Huggy
deep-reinforcement-learning
reinforcement-learning
ML-Agents-Huggy
us
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Deploy
ppo
Agent playing
Huggy
This is a trained model of a
ppo
agent playing
Huggy
using the
Unity ML-Agents Library
.
Training Results
Training steps:
2,000,000
Final mean reward:
~3.76 (std 2.01), peaked around 3.95 mid-training
Training time:
~45 minutes on a Colab GPU
Trained as part of the
Hugging Face Deep RL Course
, Bonus Unit 1
Huggy fetching the stick
Usage (with ML-Agents)
The Documentation:
https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
A
short tutorial
where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your browser:
https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
A
longer tutorial
to understand how works ML-Agents:
https://huggingface.co/learn/deep-rl-course/unit5/introduction
Resume the training
mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
Watch your Agent play
You can watch your agent
playing directly in your browser
If the environment is part of ML-Agents official environments, go to
https://huggingface.co/unity
Step 1: Find your model_id: asiful2/ppo-Huggy
Step 2: Select your
.nn /
.onnx file
Click on Watch the agent play 👀
