How to DOWNLOAD Llama 3.1 LLMs

1littlecoder
23 Jul 202404:37

TLDRThis tutorial outlines the process of downloading Llama 3.1 models, highlighting the impracticality of using the 405 billion parameter model due to its immense RAM requirements. It guides viewers to request access via Hugging Face, download the model post-approval, and use it with Transformers code or through various platforms like MAA AI, Hugging Chat, and other API providers. The speaker also mentions plans for a Google Colab tutorial and encourages user interest.

Takeaways

  • 🧠 The tutorial is about downloading and using Llama 3.1 models, with a focus on the impracticality of running the 405 billion parameter model due to immense RAM requirements.
  • 🚫 Running the 405 billion parameter model requires 8810 GB of RAM for full precision and 203 GB for quantization, making it nearly impossible for local inference.
  • 🔗 To access Llama 3.1 models, one must visit a provided link to Hugging Face and create an account if they don't have one.
  • 📝 After reaching the Llama 3.1 landing page, users need to fill out a form with details like name, affiliation, date of birth, and country to request model access.
  • ⏳ Approval for model access may take some time and is not automated, requiring users to wait for approval before downloading the model.
  • 📚 Once approved, users can download the model using a simple code snippet provided by the Transformers library.
  • 🔧 The tutorial suggests that the model can be run on Google Colab without quantization, and a separate tutorial for this might be created.
  • 🌐 MAA AI offers a cloud version of the model, accessible through a platform that requires logging in, which the presenter avoids by not having a Facebook account.
  • 🐍 The presenter demonstrates the model's capabilities by having it create a snake game in Python through a chat interface.
  • 📲 The model is also accessible via WhatsApp for users in the US, appearing as a contact named 'Meta AI'.
  • 🤖 Hugging Chat and other platforms like Grock, Together AI, and Fireworks AI offer the model through their APIs, with Hugging Chat featuring the 405 billion parameter model by default.
  • 📝 The presenter emphasizes the importance of obtaining model access first, as it's a prerequisite for downloading and using the model effectively.

Q & A

  • What is the main topic of the tutorial?

    -The main topic of the tutorial is how to download and use Llama 3.1 models.

  • Why is it not feasible to run the 405 billion parameter model locally?

    -It is not feasible to run the 405 billion parameter model locally due to the massive amount of RAM required. For full precision 16-bit, you need 8810 GB, for 8-bit precision you need 405 GB, and even with quantization you still need 203 GB of RAM.

  • What is the first step to access Llama 3.1 models?

    -The first step to access Llama 3.1 models is to go to the link provided in the YouTube description, which leads to the Hugging Face website. If you don't have an account, you need to create one.

  • What information is required to fill out the form on the Hugging Face Llama 3.1 landing page?

    -The form requires details like your name, affiliation, date of birth, and country.

  • How long does it typically take to get approval to access the model?

    -The script mentions that it takes a bit of time to get approval, but it does not specify an exact timeframe.

  • What is the process of downloading the model after getting approval?

    -After getting approval, you can access and download the model using the Transformers library in a simple code snippet.

  • Can the model be run on Google Colab without any quantization?

    -Yes, the model can be run on Google Colab without any quantization, as mentioned in the script.

  • What is the process of running the model on a cloud platform like MAA AI?

    -You can go to the MAA AI platform, log in (or continue without logging in), and start chatting with the model to run it.

  • How can you access the Llama 3.1 model on WhatsApp?

    -If you are in the US, you can try out the model using WhatsApp by seeing the Meta AI icon as one of your contacts.

  • What other platforms provide access to the Llama 3.1 model?

    -Other platforms that provide access to the Llama 3.1 model include Hugging Chat, Grock, Together AI, and Fireworks AI.

  • What is the next step the creator plans to take after this tutorial?

    -The creator plans to put together a separate Google Colab tutorial and is seeking interest from the audience.

Outlines

00:00

🤖 Downloading and Using LLaMA 3.1 Models

This paragraph provides a tutorial on downloading and using the LLaMA 3.1 models. It clarifies that the 405 billion parameter model is impractical due to the massive RAM requirements, which range from 8810 GB for full precision to 203 GB for quantized precision. The speaker guides the user to the Hugging Face website for model access, emphasizing the need for an account and the process of filling out a form for approval. Once approved, users can download and utilize the model with Transformers code, run it on Google Colab, or interact with it through various platforms like MAA AI, WhatsApp, and Hugging Chat, which may currently be overloaded due to high demand.

Mindmap

Keywords

💡Llama 3.1

Llama 3.1 refers to a series of large language models developed by Meta AI. The term is central to the video's theme as it discusses the process of downloading and using these models. The script mentions different versions of Llama, including a 405 billion parameter model, indicating the scale and complexity of these AI systems.

💡Parameter

In the context of AI models, a 'parameter' is a variable that the model learns to adjust during training to minimize a loss function. The script emphasizes the vast number of parameters in Llama 3.1 models, highlighting the models' size and computational requirements.

💡RAM

RAM, or Random Access Memory, is the hardware in a computer that temporarily stores data. The video script discusses the significant amount of RAM required to run the Llama 3.1 models, especially the 405 billion parameter model, which underscores the models' resource-intensive nature.

💡Hugging Face

Hugging Face is a company that provides a platform for machine learning models, including the Llama 3.1 models. The script instructs viewers to visit Hugging Face to request access to the models, making it a key part of the tutorial.

💡Model Access

Model access refers to the permission or ability to use a specific AI model. The video explains that viewers need to request access to the Llama 3.1 models on Hugging Face, which involves filling out a form and waiting for approval.

💡Transformers

In the context of the video, Transformers is a library used for state-of-the-art natural language processing. The script provides a simple code example using Transformers to load and run the Llama 3.1 model, illustrating its application in practice.

💡Google Colab

Google Colab is a cloud-based platform for machine learning education and research, which allows users to run Jupyter notebooks in the cloud. The video mentions using Google Colab to run the Llama 3.1 models without quantization, indicating a method to utilize these models with limited hardware resources.

💡Quantization

Quantization in AI refers to the process of reducing the precision of the numbers used in a model to save memory and computation. The script discusses different levels of quantization for the Llama 3.1 models, such as 8-bit precision and GPTQ, to manage the models' large memory requirements.

💡API Providers

API, or Application Programming Interface, providers offer access to software functionalities through interfaces. The video mentions several API providers that offer access to the Llama 3.1 models, such as MAA AI, Grock, and Together AI, indicating different platforms where the models can be utilized.

💡Overloaded

In the context of the video, 'overloaded' refers to a situation where a system, such as an AI model, is experiencing high demand and is unable to handle all requests efficiently. The script mentions that the model might be overloaded when many people are trying to access it at once.

💡Hugging Chat

Hugging Chat is a service provided by Hugging Face that allows users to interact with AI models through a chat interface. The video script suggests using Hugging Chat to test the Llama 3.1 model's capabilities, such as creating jokes about Elon Musk.

Highlights

Tutorial on downloading and using Llama 3.1 models.

Cannot use the 405 billion parameter model due to massive RAM requirements.

For local inference, 405 billion parameter model needs 8810 GB of RAM with full precision.

8-bit precision reduces RAM requirement to 405 GB.

Quantization with gptq bits and bytes still requires 203 GB of RAM.

Instructions on accessing the Llama 3.1 models via Hugging Face.

Need to create an account on Hugging Face if you don't have one.

Fill out a form on the Llama 3.1 landing page for model access.

Approval process for model access may take some time.

Once approved, you can download and use the model with Transformers.

Demonstration of running the model on Google Colab without quantization.

Introduction to running the model with a cloud version through MAA AI.

MAA AI's platform allows chatting with the model without logging in.

MAA AI claims to run the 405 billion parameter model.

Model also accessible via WhatsApp for users in the US.

Hugging chat HF, doco chat, provides access to the 405 billion parameter model.

Model availability through other API providers like grock together AI and fireworks Ai.

Reminder to get access first to avoid difficulties in using the model.

Promise of a separate Google Colab tutorial for interested viewers.

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