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TootToot
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ppo-Huggy

Reinforcement Learning
ml-agents
TensorBoard
ONNX
Huggy
deep-reinforcement-learning
ML-Agents-Huggy
Model card Files Metrics Community
TootToot commited on
Commit
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1 Parent(s): b170c42

Huggy

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Files changed (29) hide show
  1. Huggy.onnx +1 -1
  2. Huggy/Huggy-1199993.onnx +3 -0
  3. Huggy/Huggy-1199993.pt +3 -0
  4. Huggy/Huggy-1399936.onnx +3 -0
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  26. README.md +14 -8
  27. run_logs/Player-0.log +15 -15
  28. run_logs/timers.json +143 -143
  29. run_logs/training_status.json +59 -59
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README.md CHANGED
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8
  ---
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10
  # **ppo** Agent playing **Huggy**
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- This is a trained model of a **ppo** agent playing **Huggy** using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
12
-
 
13
  ## Usage (with ML-Agents)
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- The Documentation: https://github.com/huggingface/ml-agents#get-started
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- We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
16
 
 
 
 
 
 
17
 
18
  ### Resume the training
19
- ```
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  mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
21
  ```
 
22
  ### Watch your Agent play
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- You can watch your agent **playing directly in your browser:**.
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-
25
- 1. Go to https://huggingface.co/spaces/unity/ML-Agents-Huggy
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  2. Step 1: Find your model_id: TootToot/ppo-Huggy
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  3. Step 2: Select your *.nn /*.onnx file
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  4. Click on Watch the agent play 👀
 
8
  ---
9
 
10
  # **ppo** Agent playing **Huggy**
11
+ This is a trained model of a **ppo** agent playing **Huggy**
12
+ using the [Unity ML-Agents Library](https://github.com/Unity-Technologies/ml-agents).
13
+
14
  ## Usage (with ML-Agents)
15
+ The Documentation: https://unity-technologies.github.io/ml-agents/ML-Agents-Toolkit-Documentation/
 
16
 
17
+ We wrote a complete tutorial to learn to train your first agent using ML-Agents and publish it to the Hub:
18
+ - A *short tutorial* where you teach Huggy the Dog 🐶 to fetch the stick and then play with him directly in your
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+ browser: https://huggingface.co/learn/deep-rl-course/unitbonus1/introduction
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+ - A *longer tutorial* to understand how works ML-Agents:
21
+ https://huggingface.co/learn/deep-rl-course/unit5/introduction
22
 
23
  ### Resume the training
24
+ ```bash
25
  mlagents-learn <your_configuration_file_path.yaml> --run-id=<run_id> --resume
26
  ```
27
+
28
  ### Watch your Agent play
29
+ You can watch your agent **playing directly in your browser**
30
+
31
+ 1. If the environment is part of ML-Agents official environments, go to https://huggingface.co/unity
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  2. Step 1: Find your model_id: TootToot/ppo-Huggy
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  3. Step 2: Select your *.nn /*.onnx file
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  4. Click on Watch the agent play 👀
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