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JonusNattapong
/
romeo-v8-super-ensemble-trading-ai

Scikit-learn
English
trading
finance
xauusd
gold
forex
machine-learning
ensemble
super-ensemble
xgboost
lightgbm
catboost
neural-network
tensorflow
Model card Files Files and versions
xet
Community

Instructions to use JonusNattapong/romeo-v8-super-ensemble-trading-ai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Scikit-learn

    How to use JonusNattapong/romeo-v8-super-ensemble-trading-ai with Scikit-learn:

    from huggingface_hub import hf_hub_download
    import joblib
    model = joblib.load(
    	hf_hub_download("JonusNattapong/romeo-v8-super-ensemble-trading-ai", "sklearn_model.joblib")
    )
    # only load pickle files from sources you trust
    # read more about it here https://skops.readthedocs.io/en/stable/persistence.html
  • Notebooks
  • Google Colab
  • Kaggle
romeo-v8-super-ensemble-trading-ai / backtest_results_romeo_v8
68.8 kB
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  • 1 contributor
History: 3 commits
JonusNattapong's picture
JonusNattapong
Upload backtest_results_romeo_v8/romeo_summary_15m.json with huggingface_hub
48ff61a verified 11 months ago
  • romeo_signals_15m.csv
    51.3 kB
    Upload backtest_results_romeo_v8/romeo_signals_15m.csv with huggingface_hub 11 months ago
  • romeo_summary_15m.json
    673 Bytes
    Upload backtest_results_romeo_v8/romeo_summary_15m.json with huggingface_hub 11 months ago
  • romeo_trades_15m.csv
    16.8 kB
    Upload backtest_results_romeo_v8/romeo_trades_15m.csv with huggingface_hub 11 months ago