How to Run LLAMA 3 on your PC or Raspberry Pi 5

Gary Explains
23 Apr 202408:15

TLDRThe video provides a guide on how to run the LLAMA 3, a new generation of large language models developed by Meta (Facebook), locally on a PC or a Raspberry Pi 5. Two versions of LLAMA 3 are discussed: an 8 billion parameter version and a 70 billion parameter version. The 8 billion parameter model is highlighted for its efficiency and performance, trained with 1.3 million hours of GPU time and surpassing the capabilities of LLAMA 2. The video demonstrates using LM Studio for Windows to download and interact with the LLAMA 3 model, showcasing its knowledge and answering questions. Additionally, the video covers running LLAMA 3 on a Raspberry Pi 5 using the OLLama project, which is also compatible with Mac OS and Linux. The host, Gary Sims, invites viewers to share their thoughts on LLAMA 3 and running large language models on various devices.

Takeaways

  • 🚀 Facebook (Meta) has launched LLaMA 3, a next-generation large language model available in two sizes: an 8 billion parameter version and a 70 billion parameter version.
  • 💻 The video focuses on running the 38 billion parameter version of LLaMA 3 locally due to hardware limitations for the 70 billion parameter version.
  • ⏱️ The 8 billion parameter version of LLaMA 3 was trained using 1.3 million hours of GPU time, outperforming LLaMA 2 models.
  • 📈 LLaMA 3's 8 billion parameter version is 34% better than the 7 billion parameter LLaMA 2 and 14% better than the 13 billion parameter LLaMA 2.
  • 📚 The knowledge cutoff date for the 38 billion parameter version of LLaMA 3 is March 2023, and for the 70 billion parameter version, it's December 2023.
  • 📘 LM Studio is used to run LLaMA 3 on Windows, with download options available for various platforms including M1/M2/M3 processors, Windows, and Linux.
  • 🔍 LM Studio provides a chat interface similar to chat GPT for local interaction with the LLaMA 3 model.
  • 📱 The video also demonstrates running LLaMA 3 on a Raspberry Pi 5 using the Ollama project, which is available for Mac OS, Linux, and Windows.
  • 🔗 The Ollama project allows for the download and installation of LLaMA 3 directly on a Raspberry Pi 5, providing a command-line interface for interaction.
  • 🧐 LLaMA 3 is capable of understanding and responding to complex questions and lateral thinking puzzles, showcasing its depth of knowledge.
  • 🌐 The video encourages viewers to experiment with LLaMA 3 and other models locally on various devices, such as laptops, desktops, and Raspberry Pi.

Q & A

  • What are the two sizes of LLAMA 3 that have been launched by Meta?

    -The two sizes of LLAMA 3 are an 8 billion parameter version and a 70 billion parameter version.

  • Why is the 8 billion parameter version of LLAMA 3 chosen for local running in the video?

    -The 8 billion parameter version is chosen because a normal desktop or laptop isn't capable of running the larger 70 billion parameter version due to its size.

  • How much GPU time was used to train the 8 billion parameter version of LLAMA 3?

    -The 8 billion parameter version was trained using 1.3 million hours of GPU time.

  • What is the performance comparison of the 8 billion parameter version of LLAMA 3 against LLAMA 2?

    -It's 34% better than the 7 billion parameter version of LLAMA 2 and 14% better than the 13 billion parameter version of LLAMA 2.

  • What is the knowledge cutoff date for the 8 billion and 70 billion parameter versions of LLAMA 3?

    -The knowledge cutoff date for the 8 billion parameter version is March of 2023, and for the 70 billion parameter version, it is December of 2023.

  • Which platform is used to run LLAMA 3 in the video?

    -LM Studio is used to run LLAMA 3 on Windows, and the O Lama project is used to run it on a Raspberry Pi 5.

  • How can one download and install LM Studio on their computer?

    -One can download LM Studio from the LM Studio website by selecting the appropriate download option for their platform, installing it, and then starting the program.

  • What is the main difference between the smaller models and LLAMA 3 when it comes to information content?

    -Smaller models may lack substantial information and not be able to answer certain questions, whereas LLAMA 3, even in its 8 billion parameter version, has a greater depth of knowledge and can provide answers to more complex queries.

  • How does the chat function in LM Studio work?

    -The chat function in LM Studio provides a chat interface similar to chat GPT, allowing users to interact with the model locally after selecting the model they wish to use.

  • What is the process of running LLAMA 3 locally using the O Lama project?

    -One can run LLAMA 3 locally using the O Lama project by visiting the O Lama website, downloading the install script, pasting and running it on the desired platform such as a Raspberry Pi 5, and then using the command line to run LLAMA 3.

  • What kind of lateral thinking puzzle is presented in the video?

    -The lateral thinking puzzle presented is about three towels taking 3 hours to dry and questioning how long it would take for nine towels to dry, which LLAMA 3 correctly identifies as not being a simple multiplication problem.

  • What are some of the different platforms on which one can run LLAMA 3 according to the video?

    -According to the video, one can run LLAMA 3 on a Raspberry Pi, a laptop, a desktop, and on various operating systems like Mac OS, Linux, and Windows.

Outlines

00:00

🚀 Introduction to Llama 3 and Local Execution

The video introduces Llama 3, Facebook's (Meta's) latest large language model, available in 8 billion and 70 billion parameter versions. The focus is on the 8 billion parameter version, which is more manageable for local execution on a normal desktop or laptop. It is compared to Llama 2, showing significant performance improvements. The video also discusses the training time for the 8 billion parameter model and its knowledge cutoff date. The presenter plans to demonstrate running Llama 3 locally using LM Studio on Windows and a Raspberry Pi 5, with a brief mention of the availability of LM Studio for different platforms and the inclusion of other models such as Google's Meena.

05:00

🛠️ Running Llama 3 on Raspberry Pi 5 with O Lama Project

The second paragraph details how to run Llama 3 locally using the O Lama project. It provides instructions for downloading and installing the project on a Raspberry Pi 5, emphasizing the transparency of the installation script. The video demonstrates the capabilities of Llama 3 by asking it a lateral thinking puzzle about drying towels, which it answers correctly. The presenter highlights the versatility of running Llama 3 on various devices, including a Raspberry Pi, laptop, or desktop, and encourages viewers to experiment with the model. The video concludes with a call to action for viewers to share their thoughts on Llama 3 and subscribe to the channel for more content.

Mindmap

Keywords

💡LLAMA 3

LLAMA 3 is a next-generation large language model developed by Meta (formerly Facebook). It is available in two sizes: an 8 billion parameter version and a 70 billion parameter version. The model is designed to process and generate human-like language, making it useful for various AI applications. In the video, the focus is on running the 8 billion parameter version locally due to hardware limitations for the larger model.

💡Parameter Version

A parameter version refers to a specific configuration of a machine learning model, defined by the number of parameters it contains. Parameters are the model's learned variables that it uses to make predictions or generate outputs. The larger the number of parameters, the more complex the model can be, typically leading to better performance at the cost of increased computational requirements.

💡LM Studio

LM Studio is a platform or software application mentioned in the video that allows users to run and interact with language models like LLAMA 3 on their local machines. It provides a user interface for downloading models, selecting them, and engaging in a chat-like interface to communicate with the AI.

💡Raspberry Pi 5

The Raspberry Pi 5 is a small, low-cost, single-board computer developed by the Raspberry Pi Foundation. It is used in the video to demonstrate the capability of running the LLAMA 3 model locally on a device that is not a traditional desktop or laptop. This showcases the accessibility and versatility of the LLAMA 3 model.

💡Knowledge Cut-off Date

The knowledge cut-off date refers to the date until which the information and training data of a language model is considered up-to-date. For LLAMA 3, the cut-off dates are March 2023 for the 8 billion parameter version and December 2023 for the 70 billion parameter version, indicating the latest information the models have been trained on.

💡GPU Time

GPU time stands for Graphics Processing Unit time and refers to the amount of time a GPU is used for processing tasks, particularly in machine learning and deep learning. In the context of the video, the 8 billion parameter version of LLAMA 3 was trained using 1.3 million hours of GPU time, highlighting the intensive computational effort required to train such models.

💡Model Performance

Model performance in the context of AI refers to how well a model accomplishes its tasks, such as language processing or generation. The video compares the performance of LLAMA 3's 8 billion parameter version to previous versions of LLAMA, noting that it is 34% better than LLAMA 2's 7 billion parameter version and 14% better than LLAMA 2's 13 billion parameter version.

💡Chat Interface

A chat interface is a user interface that allows for communication between a user and a computer program in a conversational manner. In the video, the chat interface is used to interact with the LLAMA 3 model locally, simulating a conversation with the AI to test its knowledge and language generation capabilities.

💡Lateral Thinking Puzzle

A lateral thinking puzzle is a type of brain teaser that requires finding a solution by thinking about the problem in a creative or indirect way, rather than following a straightforward logical approach. In the video, a classic lateral thinking puzzle about drying towels is presented to the LLAMA 3 model to demonstrate its ability to understand and respond to non-linear problems.

💡Open-Source Model

An open-source model refers to a software model or application whose source code is made available to the public, allowing anyone to view, use, modify, and distribute it. In the context of the video, the smaller version of LLAMA 3 is mentioned as being available as an open-source model, which can be run on various platforms, including a Raspberry Pi 5.

💡Local Running

Local running implies executing a program or application on the user's own computer or device rather than on a remote server or cloud platform. The video discusses how to run the LLAMA 3 model locally on different devices, such as a PC, Raspberry Pi 5, or a Mac, which allows users to utilize the model without relying on an internet connection or external services.

Highlights

Meta (Facebook) has launched LLaMa 3, a next-generation large language model.

LLaMa 3 comes in two sizes: an 8 billion parameter version and a 70 billion parameter version.

The 8 billion parameter version of LLaMa 3 is more performant than LLaMa 2, with 34% improvement over the 7 billion parameter version and 14% over the 13 billion parameter version.

The 8 billion parameter version of LLaMa 3 is only 8% worse than the 70 billion parameter version of LLaMa 2.

The knowledge cutoff date for the 8 billion parameter version of LLaMa 3 is March 2023, and for the 70 billion version, it's December 2023.

LM Studio can be used to run LLaMa 3 on Windows, with download options available for various platforms including M1 processors and Linux.

LM Studio provides a chat interface similar to chat GPT for local interaction with the model.

Smaller models may lack information; for example, a 2 billion parameter model might not answer a question about Henry VII.

LLaMa 3's 8 billion parameter version can provide detailed information, such as the year Henry VII was married to Katherine of Aragon.

LLaMa 3 can answer logical questions and perform tasks like identifying the color of objects in a given scenario.

When comparing movies to Star Wars: Episode IV - A New Hope, LLaMa 3 identifies The Princess Bride as the most similar, providing reasoning behind its choice.

Another way to run LLaMa 3 locally is through the OLLaMa project, which is available for Mac OS, Linux, and Windows.

The OLLaMa project allows for installation on a Raspberry Pi 5 by running an install script.

LLaMa 3 can be run on a Raspberry Pi 5, providing a command-line chat interface for interaction.

LLaMa 3 can handle lateral thinking puzzles, understanding that the drying time of towels does not simply multiply with their number.

LLaMa 3 is available in different sizes and can be run on various devices, including Raspberry Pi, laptops, and desktops.

Gary Sims, the presenter, invites viewers to share their thoughts on LLaMa 3 and running large language models on different devices.