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license: mit
library_name: kronos-mlx
pipeline_tag: time-series-forecasting
tags:
- mlx
- apple-silicon
- finance
- kronos
- tokenizer
base_model: NeoQuasar/Kronos-Tokenizer-base
---
# Kronos-Tokenizer-base (MLX)
Apple [MLX](https://github.com/ml-explore/mlx) port of [`NeoQuasar/Kronos-Tokenizer-base`](https://huggingface.co/NeoQuasar/Kronos-Tokenizer-base) — the BSQ (Binary Spherical Quantizer) tokenizer that compresses OHLCV candlestick sequences into hierarchical discrete tokens for the [Kronos](https://github.com/shiyu-coder/Kronos) family of forecasting models.
Use it together with one of the MLX-native Kronos predictors, e.g. [`gxcsoccer/kronos-mlx-small`](https://huggingface.co/gxcsoccer/kronos-mlx-small).
## Usage
```python
from kronos_mlx import Kronos, KronosTokenizer, KronosPredictor
tokenizer = KronosTokenizer.from_pretrained("gxcsoccer/kronos-mlx-tokenizer-base")
model = Kronos.from_pretrained("gxcsoccer/kronos-mlx-small")
predictor = KronosPredictor(model, tokenizer, max_context=512)
```
## Original
- Upstream: [shiyu-coder/Kronos](https://github.com/shiyu-coder/Kronos)
- PyTorch weights: [NeoQuasar/Kronos-Tokenizer-base](https://huggingface.co/NeoQuasar/Kronos-Tokenizer-base)
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