Instructions to use Nharen/Reward_Rush_SAC_Half_Cheetah with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Nharen/Reward_Rush_SAC_Half_Cheetah with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Nharen/Reward_Rush_SAC_Half_Cheetah", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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---
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license: mit
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---
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license: mit
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tags:
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- reinforcement-learning
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- mujoco
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- halfcheetah
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- sac
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- stable-baselines3
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model-index:
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- name: Your_Model_Name_SAC_HalfCheetah-v4
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results:
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- task:
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type: reinforcement-learning
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name: reinforcement-learning
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dataset:
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name: HalfCheetah-v4
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type: HalfCheetah-v4
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metrics:
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- type: mean_reward
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value: 9692.192
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name: Avg reward
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- type: max_reward
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value: 9969.899
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name: Max reward
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- type: min_reward
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value: 9408.777
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name: Min reward
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---
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