Instructions to use callensxavier/v10g2-dqn-compiler-optimization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use callensxavier/v10g2-dqn-compiler-optimization with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="callensxavier/v10g2-dqn-compiler-optimization", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Add best CVaR-DQN model (seed 789, alpha=0.6) for the head-to-head
Browse files
v10h_cvar_dqn_seed789_alpha06_2M.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:4d83190e1d9a134c477bdb3a573a33c4aa54383ceb3ef03707f350ba83982eb9
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size 8958993
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