How to Run Llama 3 Locally on your Computer (Ollama, LM Studio)

In this video, the host guides viewers on how to run Llama 3 locally on their computer using Olllama, LM Studio, and Jan AI. The process allows users to maintain data privacy while leveraging AI capabilities. The host demonstrates the installation and use of Llama 3 on different platforms, including Mac M2, and showcases its speed and efficiency in generating responses to queries like creating a meal plan. Additionally, the video covers how to use Olllama API for terminal interactions and provides a brief look at integrating Jan AI with local endpoints. The host expresses excitement about the topic and promises more content in the future, encouraging viewers to like, share, and subscribe.

Takeaways

• 📘 To run Llama 3 locally, you can use Ollama, LM Studio, or Jan AI to maintain data privacy and utilize AI capabilities.
• 💻 Download Ollama from ama.com and run Llama 3 in your terminal to automatically download the 8 billion parameter model.
• 🚀 Ollama provides fast responses; the example given was generating a meal plan which was completed swiftly.
• 🖥️ For LM Studio, download the appropriate version for your operating system and use the interface to search and download Llama 3.
• 🔍 After downloading Llama 3 in LM Studio, you can select the model and start chatting to get responses like a meal plan.
• 🔧 Jan AI also allows local installation of Llama 3, where you can search for the model and install it for use in the chat section.
• 🔗 With Jan AI, you can choose different models for chat, though Llama 3 was mentioned as coming soon in the script.
• 📝 To use the Ollama API, install it via pip, and then write a script to load Llama 3 and ask questions, receiving responses.
• 📚 For LM Studio, you can start a local server to integrate with your API using the provided endpoint and code examples.
• 🔑 The script demonstrates using a curl command and Python code to interact with the Llama 3 model via an API.
• ⚙️ Jan AI can be integrated with your API using the Local Host 1337 endpoint, as shown in the script.
• 🎥 The video creator encourages viewers to subscribe for more content on Artificial Intelligence and thanks them for watching.

Q & A

What is the main advantage of running Llama 3 locally on your computer?

Running Llama 3 locally allows you to keep your data private and leverage the power of AI without sharing your information with external servers.

How can you download and run Llama 3 using Ollama?

You can download Ollama from ama.com, select the appropriate version for your operating system (Mac, Linux, or Windows), and then run the command 'ollama run llama 3' in your terminal to download and use the Llama 3 model.

What is the benefit of using LM Studio for running Llama 3?

LM Studio provides a user interface where you can search for and download different models, including Llama 3. It also allows you to chat with the AI model directly within the application.

How can you install Llama 3 using Jan AI?

You can download the Mac version of Jan AI, search for the Llama 3 model within the application, and install it. After installation, you can select the model and start a new chat to interact with Llama 3.

What is the process to use the Ollama API to load Llama 3 in your terminal?

First, ensure you have 'ollama' installed via pip. Then, in your code, import 'ollama', and use the 'ollama.chat' function to load the Llama 3 model and interact with it.

How do you start the local server for LM Studio?

In LM Studio, you can click on the local server icon and then click 'Start server'. This will run the server, and you can use the provided endpoint for further interactions.

What is the purpose of using the 'pip install openai' command in the context of LM Studio?

The 'pip install openai' command is used to install the OpenAI package, which is required to run the provided Python code for interacting with the Llama 3 model through LM Studio's API.

How can you integrate Jan AI with your API using a local endpoint?

You can use the local endpoint 'Local Host 1337' to integrate Jan AI with your API, allowing you to leverage the capabilities of the Llama 3 model in your applications.

What type of content does the YouTube channel mentioned in the script focus on?

The YouTube channel focuses on creating videos related to Artificial Intelligence, providing tutorials and insights into various AI models and technologies.

What is the significance of the Llama 3 8 billion parameter model?

The Llama 3 8 billion parameter model signifies a large-scale AI model with a vast number of parameters, which allows it to process and generate highly complex and nuanced responses.

How does the speed of Llama 3 compare to other models when generating responses?

The script indicates that Llama 3 is very fast in generating responses, which is impressive considering it is running on a Mac M2, suggesting it performs well even on consumer-grade hardware.

What are the steps to get started with Llama 3 after downloading Ollama?

After downloading Ollama, you run the command 'ollama run llama 3' in your terminal, which automatically downloads the Llama 3 model. Once the model is ready, you can start asking questions and receiving responses.

Outlines

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🚀 Running Llama 3 Locally for Data Privacy and AI Power

The video introduces how to run the AI model Llama 3 locally on your computer using Olama, LM Studio, and Jan AI. This allows for maintaining data privacy while leveraging AI capabilities. The presenter, excited about the topic, guides viewers through the process of downloading and using Llama 3, starting with downloading Olama from ama.com and running the model locally. The video demonstrates the model's speed and efficiency, particularly when running on a Mac M2. It also covers installing LM Studio, searching for and downloading Llama 3, and using it to generate a meal plan. Lastly, the presenter discusses installing Jan AI, using it locally, and accessing the Llama 3 model through its chat section.

Keywords

💡Llama 3

Llama 3 refers to a specific version of an AI model, characterized by its ability to process and generate human-like text based on given prompts. In the video, it is the core technology that enables local AI applications to function, allowing users to run it on their computers for tasks such as generating meal plans or answering questions about the sky's color.

💡Ollama

Ollama is a software tool mentioned in the video that facilitates the running of the Llama 3 model locally on a user's computer. It is used to download and utilize the Llama 3 model, thus enabling users to access AI capabilities without needing to rely on cloud-based services, which can be beneficial for privacy and speed.

💡LM Studio

LM Studio is a graphical user interface (GUI) application that allows users to interact with various AI models, including Llama 3. The video demonstrates how to install and use LM Studio to search for, download, and chat with the Llama 3 model, providing a user-friendly way to leverage AI for generating responses to queries.

💡Jan AI

Jan AI is another platform or software mentioned for running AI models like Llama 3 locally. It is shown in the video as an alternative method to use Llama 3, where users can install the model and interact with it through a chat interface to get responses to their questions.

💡Local Hosting

Local hosting refers to the practice of running services, such as AI models, on a user's own computer rather than on a remote server. The video emphasizes the benefits of local hosting for Llama 3, including data privacy and potentially faster response times, as the processing is done on the user's local machine.

💡Data Privacy

Data privacy is a key concern in the context of the video, as running AI models like Llama 3 locally allows users to keep their data private. This means that sensitive information or queries do not need to be transmitted over the internet, reducing the risk of data breaches or unauthorized access.

💡AI Chat Interface

An AI chat interface is a feature provided by LM Studio and Jan AI that allows users to communicate with the AI model through a chat-like format. In the video, this interface is used to ask the Llama 3 model for a meal plan and other information, simulating a conversation with a human.

💡API (Application Programming Interface)

An API is a set of protocols and tools that allows different software applications to communicate with each other. In the context of the video, the Olllama API is used to load the Llama 3 model into a terminal for command-line interactions, demonstrating how developers can integrate AI models into their applications.

💡Parameter Model

A parameter model, specifically mentioned as the '8 billion parameter model' in the video, refers to the size and complexity of an AI model, which is determined by the number of parameters it uses to process information. Llama 3's large parameter count indicates its advanced capabilities in understanding and generating text.

💡Meal Plan Generation

Meal plan generation is an example task demonstrated in the video where the Llama 3 model is used to create a meal plan for a day. This showcases the model's ability to understand natural language requests and generate detailed, contextually appropriate responses, including ingredients and cooking instructions.

💡Code Integration

Code integration is the process of incorporating AI models into existing software codebases, as shown when the video demonstrates how to use the Olllama API and LM Studio's local server to integrate Llama 3 into custom applications. This allows developers to add AI-driven functionalities to their software.

Highlights

The video demonstrates how to run Llama 3 locally on your computer for data privacy and AI advantages.

Llama 3 can be run using Olllama, LM Studio, and Jan AI.

Downloading Olllama from ama.com provides versions for Mac, Linux, and Windows.

Running 'ollama run llama 3' in the terminal downloads the 8 billion parameter model of Llama 3.

Llama 3 offers fast responses, as demonstrated by generating a meal plan.

LM Studio provides a user interface to search and download various AI models, including Llama 3.

LM Studio allows users to chat with the AI model after it's loaded.

Jan AI can be installed and used locally, with Llama 3 support coming soon.

Jan AI's chat section enables model selection and question asking for AI responses.

Ollama API can be used to load Llama 3 in the terminal with a few lines of code.

The Olllama API example code is provided to ask why the sky is blue and receive a response.

LM Studio's local server can be started to integrate with APIs using the provided endpoint.

Jan AI can be integrated with local applications using the Local Host 1337 endpoint.

The video creator plans to produce more content on similar topics.

The video encourages viewers to like, share, and subscribe for updates on AI topics.

The presenter is excited about the capabilities of running Llama 3 locally and its potential.

The video provides a step-by-step guide on how to run Llama 3 locally for various platforms.

The speed and efficiency of Llama 3 are showcased through real-time demonstrations.