In 2024, Meta released Llama 3.1 405B as a groundbreaking open-source AI model leading the way in innovation. The 405B model offers superior flexibility, control and cutting-edge features so developers can explore advanced workflows like easy-to-use synthetic data generation, follow turnkey directions for model distillation and enable seamless RAG operations. If you are planning to deploy the Llama 3.1 405B model but are unsure how to start, check out our latest tutorial below.
In our tutorial, we provide a step-by-step guide to deploying the billion-parameter Llama 3.1 model.
Llama 3.1 405B is Meta's most advanced open-source large language model, featuring 405 billion parameters. It excels in multilingual dialogue, outperforming numerous industry benchmarks for both closed and open-source conversational AI models. The model supports multiple languages, enhancing its applicability across diverse linguistic contexts. It can process up to 128,000 tokens, so it handles extensive textual data and maintains coherence over long passages.
The Llama 3.1 405B comes with new capabilities, including:
Multilingual Support: Llama 3.1 405B supports multiple languages, including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai, enhancing its applicability across diverse linguistic contexts.
Extended Context Length: The model can process up to 128,000 tokens, enabling it to handle extensive textual data and maintain coherence over long passages.
Tool Usage Capabilities: Llama 3.1 405B is designed to utilise external tools, expanding its functionality beyond text generation.
Open Source Accessibility: As an open-source model, Llama 3.1 405B is accessible for research and development, promoting transparency and innovation in AI applications.
Synthetic Data Generation: Generates synthetic data to address privacy and data scarcity challenges.
Now, let's walk through the step-by-step process of deploying Llama 3.1 405B on Hyperstack.
Initiate Deployment
Select Hardware Configuration
For Llama 3.1 405B hardware requirements, go to the hardware options and choose the either "8xNVIDIA A100 PCIe or 8xNVIDIA H100 SXM5" flavour.
Choose the Operating System
Select a keypair
Network Configuration
Enable SSH Access
Configure Additional Settings
Please note: this cloud-init script will only enable the API once for demo-ing purposes. For production environments, consider using secure connections, secret management, and monitoring for your API.
Review and Deploy
After deploying your VM, the cloud-init script will begin its work. This process typically takes about 20 minutes. During this time, the script performs several crucial tasks:
While waiting, you can prepare your local environment for SSH access and familiarise yourself with the Hyperstack dashboard.
Once the initialisation is complete, you can access your VM:
Locate SSH Details
Connect via SSH
To access and experiment with Meta's latest model, SSH into your machine after completing the setup. If you are having trouble connecting with SSH, watch our recent platform tour video (at 4:08) for a demo. Once connected, use this API call on your machine to start using the Llama 3.1 405B:
MODEL_NAME="meta-llama/Meta-Llama-3.1-405B-Instruct-FP8"
curl -X POST http://localhost:8000/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "'$MODEL_NAME'",
"messages": [
{
"role": "user",
"content": "Hello, how are you?"
}
]
}'
IMPORTANT: We are deploying the quantised FP8 model version to enable it to fit within a single node.
If the API is not working after ~10 minutes, please refer to our 'Troubleshooting Llama 3.1 405B section below.
If you are having any issues, please follow the following instructions:
SSH into your VM.
Check the cloud-init logs with the following command: cat /var/log/cloud-init-output.log
When you're finished with your current workload, you can hibernate your VM to avoid incurring unnecessary costs:
Hyperstack is a cloud platform designed to accelerate AI and machine learning workloads. Here's why it's an excellent choice for deploying Llama 3.1 405B:
Explore our Llama Tutorials Series Below!
Want to get started with other popular Meta Llama models? Check out our comprehensive tutorials below!
Llama 3.1 405B is Meta's top open-source language model with 405 billion parameters. It excels in multilingual dialogue, surpassing many benchmarks. It supports multiple languages and processes up to 128,000 tokens, handling extensive data and maintaining coherence.
The latest Llama 3.1 405B comes with new capabilities, including:
Multilingual Support: Llama 3.1 405B supports languages like English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai, broadening its use.
Extended Context Length: It processes up to 128,000 tokens, handling large data and maintaining coherence.
Tool Usage Capabilities: Designed to use external tools, enhancing functionality.
Open Source Accessibility: As open-source, it's available for research, promoting transparency and innovation.
Synthetic Data Generation: Creates synthetic data to tackle privacy and scarcity issues.
Yes, Llama 3.1 405B supports an expanded context of up to 128k tokens, making it capable of handling larger datasets and documents.
You can deploy Llama 3.1 405B by launching a virtual machine with an NVIDIA A100 GPU, configuring the environment, and using cloud-init scripts for setup.
Hyperstack provides access to powerful GPUs like the NVIDIA A100, easy deployment, scalability, and cost-effective GPU pricing, making it ideal for running Llama 3.1 405B.
