Scikit-learn
English
trading
finance
gold
xauusd
forex
algorithmic-trading
smart-money-concepts
smc
xgboost
machine-learning
backtesting
technical-analysis
multi-timeframe
intraday-trading
high-frequency-trading
Eval Results (legacy)
Instructions to use JonusNattapong/xauusd-trading-ai-smc-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use JonusNattapong/xauusd-trading-ai-smc-v2 with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("JonusNattapong/xauusd-trading-ai-smc-v2", "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
Upload README.md with huggingface_hub
Browse files
README.md
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# XAUUSD Multi-Timeframe Trading AI Model
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