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lc2004/
kronos_tokenizer_base_BTCUSDT_4h_finetune

Name: kronos_tokenizer_base_BTCUSDT_4h_finetune
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BTCUSDT 4-Hour Tokenizer

Tokenizer Description

This is a specialized tokenizer designed for time-series cryptocurrency data encoding, specifically fine-tuned for BTCUSDT (Bitcoin/USDT) 4-hour candlestick data. It converts numerical trading data (OHLCV - Open, High, Low, Close, Volume) into token representations suitable for transformer-based models.

Tokenizer Details

Type: Numeric Time-Series Tokenizer
Vocabulary Size: Model-specific
Input Format: BTCUSDT candlestick data (OHLCV)
Output: Token sequences for model inference
Framework: Hugging Face Transformers compatible
Time Granularity: 4-hour candlesticks

Purpose

This tokenizer is used to preprocess historical BTCUSDT 4-hour trading data before feeding it into the fine-tuned prediction model. It handles:

Price normalization: Converts raw price values to a standardized token space
Volume encoding: Encodes trading volume information
Temporal sequences: Preserves time-series relationships in medium-term data
Model compatibility: Ensures proper input format for the BTCUSDT 4h fine-tuned model

How to Use

Installation

pip install transformers torch

Loading the Tokenizer

python

from transformers import AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("lc2004/kronos_tokenizer_base_BTCUSDT_4h_finetune")

Tokenizing BTCUSDT Data

python

# Example: Tokenize BTCUSDT candlestick data
candlestick_data = "BTCUSDT 4h: Open=45230.5, High=45600.2, Low=45100.3, Close=45450.8, Volume=9382.45"

tokens = tokenizer.encode(candlestick_data, return_tensors="pt")
print(tokens)

# Decode tokens back to readable format
decoded = tokenizer.decode(tokens[0])
print(decoded)

Integration with Model

python

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("lc2004/kronos_tokenizer_base_BTCUSDT_4h_finetune")
model = AutoModelForCausalLM.from_pretrained("lc2004/kronos_base_model_BTCUSDT_4h_finetune")

# Prepare data
historical_data = "OHLCV data here..."
tokens = tokenizer.encode(historical_data, return_tensors="pt")

# Get predictions
outputs = model.generate(tokens, max_length=50)
predictions = tokenizer.decode(outputs[0])

Technical Specifications

Compatible with: BTCUSDT 4-Hour Fine-tuned Model
Data Format: Open, High, Low, Close, Volume (OHLCV)
Time Granularity: 4-hour candlesticks
Supported Operations: Encoding, decoding, tokenization
Framework: PyTorch / TensorFlow compatible
Prediction Window: Up to 48 periods (192 hours / 8 days)

Training Data

Dataset: BTCUSDT 4-hour historical candles
Source: Cryptocurrency exchange data
Time Coverage: Historical trading data up to October 2025
Data Points: Thousands of 4-hour candles
Use Case: Medium-term price forecasting

Limitations

Specialized for BTCUSDT: Not recommended for other cryptocurrency pairs or timeframes
4-Hour Granularity: Designed specifically for 4-hour candlestick data
Numeric Focus: Optimized for OHLCV data format
Normalization: Assumes price ranges similar to historical BTCUSDT data
Medium-term Optimized: Best for 3-7 day forecasting horizons

Usage Notes

⚠️ Important:

This tokenizer should be used exclusively with the BTCUSDT 4h fine-tuned model
Do not use this tokenizer with other models or datasets
Ensure your input data follows the OHLCV format
Maintain consistent data normalization across datasets
Use with 4-hour candlestick data only for optimal results

Related Models

Fine-tuned Model: BTCUSDT 4h Fine-tuned Model
Base Model: Kronos
1h Counterpart: BTCUSDT 1h Tokenizer

License

This tokenizer is released under the MIT License.

Citation

If you use this tokenizer, please cite:

bibtex

@misc{btcusdt_4h_tokenizer_2025,
  title={BTCUSDT 4-Hour Tokenizer},
  author={Liucong},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/lc2004/kronos_tokenizer_base_BTCUSDT_4h_finetune}}
}

Acknowledgments

Base framework: Hugging Face Transformers
Compatible with: BTCUSDT 4h Fine-tuned Model
Original Kronos Framework: shiyu-coder/Kronos

Contact & Support

For questions:

GitHub: Kronos-Btc-finetune
Hugging Face: lc2004

Last Updated: October 23, 2025