Instructions to use Subhash3008/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use Subhash3008/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="Subhash3008/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
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Download README.md from Subhash3008/a2c-PandaReachDense-v3: direct link, hf CLI and curl.
- Browser
- Download file 696 Bytes
-
https://huggingface.co/Subhash3008/a2c-PandaReachDense-v3/resolve/main/README.md
- Command line
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hf download hf://Subhash3008/a2c-PandaReachDense-v3/README.md
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curl -L -o README.md https://huggingface.co/Subhash3008/a2c-PandaReachDense-v3/resolve/main/README.md
696 Bytes
| tags: | |
| - reinforcement-learning | |
| - PandaReachDense-v3 | |
| - stable-baselines3 | |
| - deep-rl-course | |
| model-index: | |
| - name: a2c-PandaReachDense-v3 | |
| results: | |
| - task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: PandaReachDense-v3 | |
| type: PandaReachDense-v3 | |
| metrics: | |
| - type: mean_reward | |
| value: -0.3 +/- 0.05 | |
| name: mean_reward | |
| # A2C PandaReachDense-v3 | |
| This is a trained model for the **Hugging Face Deep Reinforcement Learning Course**. | |
| - **Environment**: `PandaReachDense-v3` | |
| - **Library**: `stable-baselines3` | |
| - **Evaluation Score**: `-0.3 +/- 0.05` | |
| Trained and submitted by **Subhash3008**. | |