DeepSeek-R1 on Amazon Bedrock

This repository will guide you through the process of importing and using the distilled DeepSeek-R1-Distill-Llama-8B model based on Llama-3.1-8B as the base model from Hugging Face on Amazon Bedrock.

To learn more about DeepSeek-R1, please visit DeepSeek.

For detailed paper walkthrough on DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning, check out this paper read on DeepSeek-R1 by Umar Jamil

Prerequisites

• AWS Account with Bedrock access
• Python environment with the following packages:
  • huggingface_hub
  • boto3

Setup Process

1. Download Model Weights

   • The model weights are downloaded from Hugging Face Hub
   • Model used: deepseek-ai/DeepSeek-R1-Distill-Llama-8B

2. Upload to S3

   • Model weights are uploaded to an S3 bucket
   • Target path: s3://[your-bucket]/models/DeepSeek-R1-Distill-Llama-8B/

3. Import to Amazon Bedrock

   • Navigate to AWS Console > Bedrock > Foundation Models > Imported Models
   • Click "Import Model"
   • Name the model (e.g., my-DeepSeek-R1-Distill-Llama-8B)
   • Provide the S3 location of the model weights
   • Wait for successful import
   • Note down the Model ARN for API calls

Usage

Run the Jupyter notebook deepseek-bedrock.ipynb for detailed implementation.

AWS Guide: https://community.aws/content/2sECf0xbpgEIaUpAJcwbrSnIGfu/deploying-deepseek-r1-model-on-amazon-bedrock