Ollama: Locally Installed LLM

Introducing Ollama

Ollama is a lightweight framework for running local language models. This framework bundles the model's weights, settings, and datasets into a single, unified package, designed for optimization across various AI applications.

Installation Guide

You can download the installation files for Mac, Linux, and Windows from the Ollama homepage.

https://ollama.com/download

Getting Started

Once the installation is complete, run the Ollama app.

You can enter the following commands in the terminal:

Ollama also provides an API for more detailed interactions. For more information, visit:

https://github.com/ollama/ollama/blob/main/docs/api.md

Selecting an LLM Model

Ollama supports various models, among which the llama-3 8B model, with its 8 billion parameters, excels in complex context understanding and problem-solving. The performance of each model can vary depending on the number of parameters and training data, so it's important to choose one that suits your purpose.

https://ollama.com/library

The llama-3 8B model offers performance similar to GPT-3.5.

Document Upload and Chat UI

Using tools like PrivateGPT, you can interact with Ollama's LLM through a chat UI.
PrivateGPT GitHub

Setting up a Conda Environment

• Create a new environment: conda create -n privategpt python=3.11
• Activate the environment: conda activate privategpt

Installing PrivateGPT

• Clone the repository: git clone https://github.com/imartinez/privateGPT
• Install Poetry: pip install poetry
• Install Make: brew install make
• Install dependencies: poetry install --extras "ui embeddings-huggingface llms-llama-cpp vector-stores-qdrant
• llms-ollama embeddings-ollama"
• Configure settings: settings-ollama.yaml

To use the document upload feature, you need to install Ollama's nomic-embed-text model.

• Run: PGPT_PROFILES=ollama make run

Conclusion

Using Ollama allows you to experience powerful natural language processing capabilities while maintaining privacy and data security. This is a significant advantage, especially in businesses or research where data sensitivity is critical.
Learn how to use Ollama and run your own LLM locally. Don't miss the opportunity to directly control high-performance natural language processing capabilities and see the results instantly.