Instructions to use mkahari/RL_testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mkahari/RL_testing with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mkahari/RL_testing", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from mkahari/RL_testing: direct link, hf CLI and curl.
- Browser
- Download file 722 Bytes
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https://huggingface.co/mkahari/RL_testing/resolve/main/README.md
- Command line
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hf download hf://mkahari/RL_testing/README.md
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curl -L -o README.md https://huggingface.co/mkahari/RL_testing/resolve/main/README.md
722 Bytes
| tags: | |
| - Taxi-v3 | |
| - q-learning | |
| - reinforcement-learning | |
| - custom-implementation | |
| model-index: | |
| - name: RL_testing | |
| results: | |
| - task: | |
| type: reinforcement-learning | |
| name: reinforcement-learning | |
| dataset: | |
| name: Taxi-v3 | |
| type: Taxi-v3 | |
| metrics: | |
| - type: mean_reward | |
| value: 7.50 +/- 2.70 | |
| name: mean_reward | |
| verified: false | |
| # **PPO** Agent playing **LunarLander-v2** | |
| This is a trained model of a **PPO** agent playing **LunarLander-v2** | |
| using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3). | |
| ## Usage (with Stable-baselines3) | |
| TODO: Add your code | |
| ```python | |
| from stable_baselines3 import ... | |
| from huggingface_sb3 import load_from_hub | |
| ... | |
| ``` | |