avirup005

Ollama: Get Started with Llama 3.3 and Other LLMs 🚀

Table of Contents

• Overview
• Supported Models
• Installation
• Usage
• Contributing
• License
• Contact

Overview

Ollama is a robust framework designed to help you get up and running with various large language models (LLMs). It supports models like Llama 3.3, DeepSeek-R1, Phi-4, Gemma 3, and Mistral Small 3.1. Whether you’re a developer, researcher, or enthusiast, Ollama simplifies the integration and utilization of these advanced models.

Supported Models

Ollama supports a variety of models, each with unique features and capabilities. Here’s a quick look:

• Llama 3.3: A state-of-the-art model known for its efficiency and performance in natural language understanding tasks.
• DeepSeek-R1: Optimized for deep learning applications, this model excels in generating context-aware responses.
• Phi-4: Focused on precision, Phi-4 is ideal for applications requiring high accuracy in language processing.
• Gemma 3: This model combines speed and performance, making it suitable for real-time applications.
• Mistral Small 3.1: A lightweight model designed for deployment in resource-constrained environments.

Installation

To install Ollama, follow these steps:

1. Clone the Repository Open your terminal and run:

   git clone https://github.com/avirup005/ollama.git
   

2. Navigate to the Directory Change into the newly created directory:

   cd ollama
   

3. Download Releases Visit the Releases section to download the latest version. Ensure you download the appropriate file for your operating system. Once downloaded, execute the file to complete the installation.

4. Install Dependencies If you’re using Go, ensure you have the necessary dependencies. Run:

   go mod tidy
   

Usage

After installation, you can start using Ollama. Here’s a simple example to get you started:

1. Load a Model You can load a model with a single command. For example, to load Llama 3.3:

   ollama load llama3
   

2. Run Inference Once the model is loaded, you can run inference. Here’s how to generate a response:

   ollama infer "What is the capital of France?"
   

3. Explore Other Commands Ollama offers various commands to manage models, run benchmarks, and more. Use the help command to explore:

   ollama help
   

Contributing

We welcome contributions from the community. If you want to contribute, please follow these steps:

1. Fork the Repository Click the “Fork” button on the top right of the repository page.

2. Create a Branch Create a new branch for your feature or bug fix:

   git checkout -b feature-name
   

3. Make Your Changes Implement your changes and commit them:

   git commit -m "Add feature description"
   

4. Push Your Changes Push your changes to your forked repository:

   git push origin feature-name
   

5. Create a Pull Request Go to the original repository and create a pull request. Provide a clear description of your changes.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For questions or support, please reach out:

• GitHub: Ollama Repository
• Email: support@ollama.com

Feel free to check the Releases section for the latest updates and files.

Topics

• deepseek
• gemma
• gemma2
• gemma3
• go
• golang
• llama
• llama2
• llama3
• llava
• llm
• llms
• mistral
• ollama
• phi3
• phi4
• qwen

Acknowledgments

We thank the contributors and the community for their support. Your feedback helps us improve and expand Ollama.

Additional Resources

• Official Documentation
• Community Forum
• GitHub Issues

Explore the power of large language models with Ollama. Start building your applications today!