For those eager to leverage the capabilities of Deepseek-R1, this article explores various methods to run it on Amazon Web Services (AWS). We'll cover approaches ranging from using Hugging Face on AWS to importing a custom model into Amazon Bedrock, and accessing it via Bedrock Marketplace and Sagemaker Jumpstart.
Many users find Claude 3.5 Sonnet on Bedrock to be a convenient tool for rapidly running labs and proof-of-concept (POC) tests. However, when it comes to Deepseek-R1, the process requires a slightly different approach since it is not natively available in the Bedrock model catalog.
Here are several strategies to get Deepseek-R1 up and running within the AWS ecosystem:
One of the quickest ways to deploy Deepseek-R1 involves using Hugging Face on AWS. Here’s how:
If you prefer to use Bedrock, you can import Deepseek-R1 as a custom model. This involves the following steps:
For more detailed instructions, refer to the official AWS documentation.
Since Deepseek-R1 was previously unavailable directly in Amazon Bedrock, consider other models that might suit your needs:
Model availability on platforms like Amazon Bedrock can change. Always refer to official AWS resources and documentation for the most accurate and up-to-date information.
By following these guidelines, you should be well-equipped to run Deepseek-R1 on AWS, choosing the method that best aligns with your project requirements and technical expertise. Happy experimenting!
