How to Run Llama 3.1 Locally on your computer? (Ollama, LM Studio)

Mervin Praison
24 Jul 202404:49

TLDRDiscover how to run the Llama 3.1 AI model locally on your computer using Ollama, LM Studio, and Jan AI. This 8 billion parameter model offers multilingual capabilities and is ideal for developers and non-developers alike. Learn to install and utilize the model for tasks like generating meal plans and writing emails, enhancing productivity without the need for internet connectivity.

Takeaways

  • 😲 The video demonstrates how to run the Llama 3.1 AI model locally on your computer.
  • 🧠 Llama 3.1 is an 8 billion parameter model, which is superior to other models like JMA 29b and mral 7B instruct.
  • 🔍 The model is capable of handling large amounts of context with 128,000 tokens and supports multilingual inputs.
  • 💻 For developers, Ollama makes it easy to integrate large language models into applications.
  • 📝 Non-developers can utilize LM Studio or Jan AI to run the model without coding.
  • 🔗 Download Ollama from the official website and run the Llama 3.1 model with simple commands.
  • 🔄 Ollama automatically downloads the model for use after installation.
  • 🌐 LM Studio offers a user-friendly interface to download and use AI models like Llama 3.1.
  • 📧 With LM Studio, users can generate content like email templates with ease.
  • 📱 Jan AI provides a mobile app for running AI models, including Llama 3.1, on-the-go.
  • 🤖 The video also mentions using Prais AI Chat to publish a chatbot within a company for internal use.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is how to run the Llama 3.1 AI model locally on your computer using Ollama, LM Studio, and Jan AI.

  • What is the parameter size of the Llama 3.1 model discussed in the video?

    -The Llama 3.1 model discussed in the video is an 8 billion parameter model.

  • How many tokens can the 8 billion parameter model handle?

    -The 8 billion parameter model can handle 128,000 tokens, allowing for the input of a large amount of context.

  • What are the advantages of using the Llama 3.1 model for non-developers?

    -Non-developers can use LM Studio or Jan AI to easily download and use the Llama 3.1 model without needing to integrate it into their own applications.

  • How can developers integrate the Llama 3.1 model into their own applications?

    -Developers can use Ollama, which is easy to use and allows the integration of large language models like Llama 3.1 into their applications.

  • What is the purpose of Ollama?

    -Ollama is used to easily run large language models like Llama 3.1 locally on your computer.

  • What does LM Studio offer to users who are not developers?

    -LM Studio offers a user-friendly interface for non-developers to download and use AI models like Llama 3.1 without needing to write code.

  • How can users access the AI chat interface in LM Studio?

    -After installing LM Studio, users can enter the model name and download the model, then use the AI chat interface to interact with the model.

  • What is Jan AI and how is it used in the context of the video?

    -Jan AI is an application that allows users to download and use AI models like Llama 3.1, similar to how LM Studio is used.

  • Can Llama 3.1 be used to create a chatbot for internal company use?

    -Yes, Llama 3.1 can be integrated with Praiser AI Chat to create a chatbot that can be used within a company.

  • How can users publish their own chatbot using Praiser AI Chat?

    -Users can install Praiser AI Chat using pip, open the UI, change the settings to use Llama 3.1, and then confirm to start using the chatbot locally.

Outlines

00:00

🤖 Running LLama 3.1 Locally

This paragraph introduces the capability of running the LLama 3.1 model, an 8 billion parameter AI assistant, entirely on your local computer. The model is noted for its superior performance compared to other large models like JMA 29b and mral 7B. The video aims to guide viewers on how to utilize this model locally using tools like olama, LM Studio, and Jan AI. The 8 billion parameter model is highlighted for its ability to handle large amounts of context and its multilingual capabilities, making it suitable for general purposes. The speaker encourages viewers to subscribe to their YouTube channel for more AI-related content and to like the video for broader reach.

Mindmap

Keywords

💡Llama 3.1

Llama 3.1 refers to an AI model with 8 billion parameters. It is a significant upgrade from its predecessors, such as the 7B and 29B models mentioned in the script. The model is capable of processing large amounts of context and is multilingual, making it versatile for various applications. In the video, the focus is on how to run this model locally on a computer, which is a key feature for those seeking a powerful AI assistant without relying on cloud-based services.

💡Local AI Model

A local AI model is one that runs on a user's personal computer rather than on a remote server. This allows for faster response times and can be more secure as the data processing happens within the user's control. In the context of the video, the speaker demonstrates how to set up and use Llama 3.1 locally, which is crucial for understanding the practical application of AI models in personal computing.

💡Ollama

Ollama is a platform mentioned in the script that allows users to run AI models locally. It simplifies the process of integrating large language models into applications. The video script shows how to use Ollama to run Llama 3.1 by typing a simple command in the terminal, which automatically downloads and prepares the model for use.

💡LM Studio

LM Studio is a tool highlighted in the video that enables non-developers to use AI models. It provides an interface where users can download and interact with various AI models, including Llama 3.1. The script demonstrates how to use LM Studio to download and utilize the model, making AI technology accessible to a broader audience.

💡Jan AI

Jan AI is another platform introduced in the script that allows users to download and use AI models. Similar to LM Studio, it provides a user-friendly interface for accessing AI models like Llama 3.1. The video explains how to use Jan AI to download the model and run it locally, emphasizing the ease of use for non-technical users.

💡Parameter

In the context of AI models, parameters are the variables that the model learns from during training. The number of parameters often correlates with the model's complexity and capability. The script mentions Llama 3.1 as having 8 billion parameters, indicating its advanced capabilities compared to models with fewer parameters.

💡Tokens

Tokens in the context of AI language models refer to the units of text, such as words or phrases, that the model processes. The script mentions that Llama 3.1 can handle 128,000 tokens, which means it can process a large amount of text at once. This is significant for tasks that require understanding extensive context.

💡Multilingual

Multilingual refers to the ability to handle multiple languages. In the video, Llama 3.1 is described as a multilingual model, which means it can process and generate text in various languages. This feature is beneficial for users who need AI assistance in different linguistic contexts.

💡AI Chat Interface

The AI chat interface is a user interface within tools like LM Studio and Jan AI that allows users to interact with AI models through text. The script demonstrates how to use this interface to ask questions and receive responses from the Llama 3.1 model, showcasing its interactive capabilities.

💡Prais AI Chat

Prais AI Chat is mentioned in the script as a tool for integrating AI chatbots within a company. It allows users to install and configure AI models, such as Llama 3.1, to be used internally. The video explains how to set up Prais AI Chat, making AI technology accessible for internal company use.

💡Productivity

Productivity in the context of the video refers to the efficiency and effectiveness with which tasks are completed. The speaker emphasizes that running Llama 3.1 locally can enhance productivity by providing a powerful AI assistant that can assist with tasks like email drafting and scheduling, as demonstrated in the script.

Highlights

How to run Llama 3.1 locally on your computer.

Llama 3.1 is an 8 billion parameter model.

Llama 3.1 is better than JMA 29b and mral 7B.

Llama 3.1 can be used as an AI assistant for general purposes.

The model can handle 128,000 tokens, allowing for large context input.

Llama 3.1 is multilingual.

Ollama can be downloaded from ama.com to run Llama 3.1.

Running Llama 3.1 locally involves typing 'ollama run llama 3.1' in the terminal.

Ollama makes it easy to use large language models in applications.

LM Studio is a tool for non-developers to use Llama 3.1.

LM Studio can be downloaded based on your operating system.

LM Studio allows you to download and use the Llama 3.1 model.

AI chat interface in LM Studio lets you interact with the model.

Jan AI is another tool to run Llama 3.1 locally.

Jan AI app can be downloaded to use Llama 3.1.

Prais AI chat can be installed via pip to run Llama 3.1 within a company.

Llama 3.1 can be integrated with company data for specific responses.

Running Llama 3.1 locally is free and can boost productivity.

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