Reinforcement Learning
stable-baselines3
finance
stock-trading
deep-reinforcement-learning
dqn
ppo
a2c
Eval Results (legacy)
Instructions to use salarking/Multi-Agent_Reinforcement_Learning_Trading_System_Models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use salarking/Multi-Agent_Reinforcement_Learning_Trading_System_Models with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="salarking/Multi-Agent_Reinforcement_Learning_Trading_System_Models", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54a214e500ce25528fc35c969e171c933e6586f6708246aee77643e26892e71f
- Size of remote file:
- 104 kB
- SHA256:
- 082ed457601973c99e60266913eb27d25adeb998142c92ce91a6d9cde1f6fc68
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