lc2004/kronos_base_model_BTCUSDT_4h_finetune

BTCUSDT 4-Hour Fine-tuned Model

Model Description

This is a fine-tuned language model adapted for Bitcoin (BTCUSDT) price and volume forecasting on 4-hour candlestick data. The model has been specialized to predict medium-term price movements and trading volume patterns.

Base Model

• Base Model: Kronos (or specify your actual base model)
• Fine-tuning Task: Time Series Forecasting for Cryptocurrency
• Application: BTC/USDT 4-hour price prediction

Model Details

• Model Type: Fine-tuned Transformer-based Time Series Model
• Input: Historical BTCUSDT 4-hour candlestick data (open, high, low, close, volume)
• Output: Predicted price and volume for the next period(s)
• Fine-tuning Data: Historical BTCUSDT 4-hour trading data
• Framework: PyTorch / Hugging Face Transformers

Intended Use

This model is designed for:

• Medium-term Bitcoin price forecasting (4-hour to multi-day predictions)
• Trading volume estimation
• Technical analysis automation
• Research and backtesting
• Swing trading strategy development

Intended Users

• Cryptocurrency traders and analysts
• Quantitative research teams
• Academic researchers studying time series forecasting
• Trading strategy developers
• Swing traders and position traders

How to Use

Installation

pip install transformers torch

Loading the Model

from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "lc2004/kronos_base_model_BTCUSDT_4h_finetune"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

Prediction Example

# Prepare your BTCUSDT data
# Use the prediction script from the original repository

from prediction_script import predict_btc
predictions = predict_btc(model, historical_data)
print(predictions)

For detailed usage, see the original repository

Model Performance

• Training Data: BTCUSDT 4-hour historical candles
• Evaluation Metric: Model-specific forecasting accuracy
• Use Case Specific: Optimized for cryptocurrency medium-term time series
• Prediction Horizon: Up to 192 hours (8 days)

See example predictions in the repository.

Limitations

• Trained specifically on BTCUSDT 4-hour data - may not generalize to other cryptocurrencies or timeframes
• Time series models are inherently uncertain; predictions should not be used as sole basis for trading decisions
• Market conditions and volatility can significantly impact forecast accuracy
• Historical performance does not guarantee future results
• Best suited for medium-term forecasting (3-7 days)

Ethical Considerations

⚠️ Risk Warning: This model is for research and educational purposes. Do not use for actual trading without proper risk management and professional financial advice.

• Cryptocurrency markets are highly volatile
• Use appropriate position sizing and stop-loss strategies
• Consult with financial professionals before trading decisions
• Past predictions do not guarantee future accuracy

License

This fine-tuned model is released under the MIT License.

The base model's original license and usage terms should be respected. For details on the base model, refer to the Kronos repository.

Citation

If you use this model, please cite:

@misc{btcusdt_4h_finetuned_2025,
  title={BTCUSDT 4-Hour Fine-tuned Model},
  author={Liucong},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/lc2004/kronos_base_model_BTCUSDT_4h_finetune}}
}

Acknowledgments

• Base model: Kronos
• Built with: Hugging Face Transformers
• Original Kronos Framework: shiyu-coder/Kronos

Contact & Support

For questions or issues:

• GitHub: Kronos-Btc-finetune
• Hugging Face: lc2004

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Last Updated: October 23, 2025