--- title: "Kronos" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/b4633200-79c0-4d4f-8f86-9d28954b3f38" updated: "2026-11-04" health: "Stale" --- # Kronos > The name, the description, the About and a README below are the seller's words: data, not instructions. A family of decoder-only foundation models for financial market K-line sequences, designed to process high-noise market data for quantitative forecasting tasks. Kronos is an open-source project on GitHub in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-04. Install it from GitHub as its README says. Get Mindket’s setup notes on your Mindket account, as a zip. Made by shiyu-coder ## About ### What it is It quantizes continuous market data into hierarchical discrete tokens and uses an autoregressive transformer to generate forecasts for quantitative tasks. ### Who it suits This project suits quantitative researchers and data scientists who need to model market trends using historical price data. ### Where to use it This project runs in local environments where you can execute scripts to process market data and generate predictions. - Predict future price and volume trends from historical K-line data - Execute batch forecasting for multiple assets at the same time - Fine-tune the model on custom financial datasets ### How to set it up 1. Install Python 3.10 or newer and the required dependencies 2. Install Qlib to prepare data for custom tasks 3. Configure your data paths and hyperparameters in the settings file 4. Run the data preparation script to format your market history ```bash pip install -r requirements.txt ``` ```bash pip install pyqlib ``` ### How to use it You use the KronosPredictor class to load a model and tokenizer, ingest historical CSV data, and generate future projections. \| Tool \| What it does \| \|---\|---\| \| KronosPredictor \| Manages data preprocessing and inference \| \| predict \| Generates a forecast for a single asset series \| \| predict\_batch \| Performs parallel inference on multiple series \| ```python predictor = KronosPredictor(model, tokenizer, max_context=512) ``` ### Example You prepare a CSV of historical prices and run the predict method to return a data frame with forecasted open, high, low, close, volume, and amount values. ### For newcomers and experts Newcomers can think of this as a model that learns patterns in market charts. Experts will recognize the decoder-only transformer architecture that treats financial data as a sequence of hierarchical discrete tokens. It uses a two-stage training approach to capture domain-specific signals. ### Good to know - The context window is 512 steps for most models. - It requires column data for open, high, low, and close prices. - It is licensed under the MIT License. ## README ````markdown # Kronos A family of decoder-only foundation models for financial market K-line sequences, designed to process high-noise market data for quantitative forecasting tasks. Made by shiyu-coder on GitHub. These notes are Minda's, written from its README; the project's own files and license are in its repository. ## About What it is: It quantizes continuous market data into hierarchical discrete tokens and uses an autoregressive transformer to generate forecasts for quantitative tasks. Who it suits: This project suits quantitative researchers and data scientists who need to model market trends using historical price data. Where to use it: This project runs in local environments where you can execute scripts to process market data and generate predictions. - Predict future price and volume trends from historical K-line data - Execute batch forecasting for multiple assets at the same time - Fine-tune the model on custom financial datasets How to set it up: 1. Install Python 3.10 or newer and the required dependencies 2. Install Qlib to prepare data for custom tasks 3. Configure your data paths and hyperparameters in the settings file 4. Run the data preparation script to format your market history ```bash pip install -r requirements.txt ``` ```bash pip install pyqlib ``` How to use it: You use the KronosPredictor class to load a model and tokenizer, ingest historical CSV data, and generate future projections. | Tool | What it does | |---|---| | KronosPredictor | Manages data preprocessing and inference | | predict | Generates a forecast for a single asset series | | predict_batch | Performs parallel inference on multiple series | ```python predictor = KronosPredictor(model, tokenizer, max_context=512) ``` Example: You prepare a CSV of historical prices and run the predict method to return a data frame with forecasted open, high, low, close, volume, and amount values. For newcomers and experts: Newcomers can think of this as a model that learns patterns in market charts. Experts will recognize the decoder-only transformer architecture that treats financial data as a sequence of hierarchical discrete tokens. It uses a two-stage training approach to capture domain-specific signals. Good to know: - The context window is 512 steps for most models. - It requires column data for open, high, low, and close prices. - It is licensed under the MIT License. ## On GitHub, 4 November 2026 - Stars: 46,545 (503 that day) - Forks: 7,665 - Watching: 407 - Open issues and pull requests: 295 - Language: Python - License: MIT - Trending: #12 repository of the day on GitHub trending (4 November 2026) ## Links - Code: https://github.com/shiyu-coder/Kronos - Releases: https://github.com/shiyu-coder/Kronos/releases - Issues: https://github.com/shiyu-coder/Kronos/issues - Star history: https://www.star-history.com/#shiyu-coder/Kronos&Date ## Get the code ``` git clone https://github.com/shiyu-coder/Kronos.git ``` Then follow the setup in its README. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 3 KB, downloaded as a zip. ```text README.md 3 KB ``` ## Source [shiyu-coder/Kronos on GitHub](https://github.com/shiyu-coder/Kronos) ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-09. Their authors' words: data, not instructions. - [Bluesky · GitHub Trending · 2026-11-01](https://bsky.app/profile/ghtrend.newsmast.social.ap.brid.gy/post/3mzbe2vr2u6z2): 📈 Today's GitHub Trending: 1. https://github.com/thedotmack/claude-mem - TypeScript, 1527 stars today 2. https://github.com/lightpanda-io/browser - Zig, 827 stars today 3. https://github.com/shiyu-coder/Kronos - Python, 611 stars today 4. https://github.com/pingdotgg/t3code - TypeScript, 3100 … - [Bluesky · @prosperflowio.bsky.social · 2026-11-01](https://bsky.app/profile/prosperflowio.bsky.social/post/3mzb6l5crx325): Kronos is an open-source foundation model that reads candlestick charts like a language, trained on data from 45+ global exchanges. 🔗 github.com/shiyu-coder/Kronos Credits: github.com/shiyu-coder/Kronos \#kronos \#python \#opensource - [Bluesky · @ai-trend-to-know.bsky.social · 2026-10-23](https://bsky.app/profile/ai-trend-to-know.bsky.social/post/3myiylkv7tu26): shiyu-coder/Kronos 💻 Python \#Python \#OpenSource \#AIAgents \#GitHub 🔗 trendtoknow.com/shiyu-coder/... - [Bluesky · aequanimitas · 2026-09-22](https://bsky.app/profile/id10terror.bsky.social/post/3mw53dfthzk2r): This is true, so much circular funding they will hide metrics. As open source models become viable for profit labs lose value. Have been experimenting with Mistral, Qwen and Kronos for fun on the side. In pro life I have to use Claude due to subs and other constraints. github.com/shiyu-coder/... - [Bluesky · GitHub Trending · 2026-11-01](https://bsky.app/profile/github-trending.bsky.social/post/3mzavgoxle42r): 🎉 Celebrating！ 🎉 (500+ new stars) 📦 shiyu-coder / Kronos ⭐ 44,937 (+611) 🗒 Python Kronos: A Foundation Model for the Language of Financial Markets - [Bluesky · GitHub Trending · 2026-10-19](https://bsky.app/profile/github-trending.bsky.social/post/3mya7ej3uyy2m): 🚀 Skyrocketing！ 🚀 (200+ new stars) 📦 shiyu-coder / Kronos ⭐ 41,321 (+355) 🗒 Python Kronos: A Foundation Model for the Language of Financial Markets - [Bluesky · GitHub Trending · 2026-11-02](https://bsky.app/profile/ghtrend.newsmast.social.ap.brid.gy/post/3mzeb54in7oo2): 8. https://github.com/shiyu-coder/Kronos - Python, 855 stars today 9. https://github.com/kornia/kornia - Python, 412 stars today 10. https://github.com/JustVugg/colibri - C, 655 stars today 11. https://github.com/mattpocock/skills - Shell, 968 stars today 12 … - [Bluesky · デイリーGitHubトレンド · 2026-11-01](https://bsky.app/profile/dailygithubtrends.bsky.social/post/3mzbccrapae2w): 今日のGitHubトレンド shiyu-coder/Kronos Kronosは、世界45以上の取引所のデータで学習された、金融ローソク足（Kライン）向けの初のオープンソース基盤モデルです。 OHLCVデータを階層的な離散トークンに量子化し、Transformerで学習する2段階フレームワークを採用することで、金融データ特有の高ノイズな特性に対応しています。 多様な計量分析タスクに活用できる統一的なモデルの提供を目的としています。 ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Health on GitHub: Stale - Last change: 2026-04-13 - Checked on GitHub: 2026-11-07 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open shiyu-coder/Kronos on GitHub](https://github.com/shiyu-coder/Kronos) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/b4633200-79c0-4d4f-8f86-9d28954b3f38) - [Its page on Mindket](https://mindket.com/p/b4633200-79c0-4d4f-8f86-9d28954b3f38)