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Kronos

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shiyu-coder/Kronos

基于45个交易所数据的金融市场K线序列基础模型。

개요

Kronos 是一系列仅解码器的基础模型,预训练自超过45个全球交易所的金融K线数据。它采用新颖的两阶段框架,包括专用分词器和自回归Transformer,能够作为统一模型处理多种量化任务,如预测。

README 미리보기

\r\n  Kronos: A Foundation Model for the Language of Financial Markets \r\n\r\n\r\n\r\n\r\n\r\n \r\n \r\n \r\n \r\n  \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n \r\n\r\n\r\n\r\n\r\n\r\n  \r\n  Deutsch | \r\n  Español | \r\n  Français | \r\n  日本語 | \r\n  한국어 | \r\n  Português | \r\n  Русский | \r\n  中文\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n> Kronos is the **first open-source foundation model** for financial candlesticks (K-lines), \r\n> trained on data from over **45 global exchanges**.\r\n\r\n\r\n\r\n\r\n## 📰 News\r\n*   🚩 **[2025.11.10]** Kronos has been accpeted by AAAI 2026.\r\n*   🚩 **[2025.08.17]** We have released the scripts for fine-tuning! Check them out to adapt Kronos to your own tasks.\r\n*   🚩 **[2025.08.02]** Our paper is now available on [arXiv](https://arxiv.org/abs/2508.02739)!\r\n\r\n\r\n\r\n## 📜 Introduction\r\n\r\n**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: \r\n1. A specialized tokenizer first quantizes continuous, multi-dimensional K-line data (OHLCV) into **hierarchical discrete tokens**. \r\n2. A large, autoregressive Transformer is then pre-trained on these tokens, enabling it to serve as a unified model for diverse quantitative tasks.\r\n\r\n\r\n    \r\n\r\n\r\n## ✨ Live Demo \r\nWe 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. \r\n\r\n**👉 [Access the Live Demo Here](https://shiyu-coder.github.io/Kronos-demo/)** \r\n\r\n## 📦 Model Zoo \r\nWe 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.\r\n\r\n| Model        | Tokenizer