shiyu-coder / Kronos

Kronos: A Foundation Model for the Language of Financial Markets 
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> Kronos is the **first open-source foundation model** for financial candlesticks (K-lines), 
> trained on data from over **45 global exchanges**.
## 📰 News
* 🚩 **[2025.11.10]** Kronos has been accpeted by AAAI 2026.
* 🚩 **[2025.08.17]** We have released the scripts for fine-tuning! Check them out to adapt Kronos to your own tasks.
* 🚩 **[2025.08.02]** Our paper is now available on arXiv!
## 📜 Introduction
**Kronos** is a family of decoder-only foundation models, pre-trained specifically for the "language" of financial markets—K-line sequences. Unlike general-purpose TSFMs, Kronos is designed to handle the unique, high-noise characteristics of financial data. It leverages a novel two-stage framework: 
1. A specialized tokenizer first quantizes continuous, multi-dimensional K-line data (OHLCV) into **hierarchical discrete tokens**. 
2. A large, autoregressive Transformer is then pre-trained on these tokens, enabling it to serve as a unified model for diverse quantitative tasks.
## ✨ Live Demo 
We have set up a live demo to visualize Kronos's forecasting results. The webpage showcases a forecast for the **BTC/USDT** trading pair over the next 24 hours. 
**👉 Access the Live Demo Here** 
## 📦 Model Zoo 
We release a family of pre-trained models with varying capacities to suit different computational and application needs. All models are readily accessible from the Hugging Face Hub.
| Model | Tokenizer | Context length | Params | Open-source |
|--------------|---------------------------------------------------------------------------------| -------------- | ------ |---------------------------------------------------------------------------|
| Kronos-mini | Kronos-Tokenizer-2k | 2048 | 4.1M | ✅ NeoQuasar/Kronos-mini |
| Kronos-small | Kronos-Tokenizer-base | 512 | 24.7M | ✅ NeoQuasar/Kronos-small |
| Kronos-base | Kronos-Tokenizer-base | 512 | 102.3M | ✅ NeoQuasar/Kronos-base |
| Kronos-large | Kronos-Tokenizer-base | 512 | 499.2M | ❌ |
## 🚀 Getting Started
### Installation
1. Install Python 3.10+, and then install the dependencies:
 [code] 
### 📈 Making Forecasts
Forecasting with Kronos is straightforward using the `KronosPredictor` class. It handles data preprocessing, normalization, prediction, and inverse normalization, allowing you to get from raw data to forecasts in just a few lines of code.
**Important Note**: The `max_context` for `Kronos-small` and `Kronos-base` is **512**. This is the maximum sequence length the model can process. For optimal performance, it is recommended that your input data length (i.e., `lookback`) does not exceed this limit. The `KronosPredictor` will automatically handle truncation for longer contexts.
Here is a step-by-step guide to making your first forecast.
#### 1. Load the Tokenizer and Model
First, load a pre-trained Kronos mod