#cloud-deployment — 1sec.ai

How to deploy and fine-tune DeepSeek models on AWS

DeepSeek models can be deployed and fine-tuned on AWS using Hugging Face's Transformers library and the SageMaker platform. This integration enables users to leverage the scalability and flexibility of AWS for their AI workloads. You can use pre-trained models or create custom models through fine-tuning. The solution provides a streamlined process for deploying and managing AI models in the cloud.

Key takeaways

DeepSeek models deployable on AWS via Hugging Face and SageMaker
Fine-tuning supported for custom model creation
Scalability and flexibility of AWS leveraged for AI workloads

HHugging Face Blog#cloud-deployment #fine-tuning #aws

modelsOct 12

Optimization story: Bloom inference

Hugging Face optimized BLOOM-176B inference to run 30% faster and cost 1.2x less on AWS. The optimization work focused on quantization, knowledge distillation, and model pruning. You can now deploy BLOOM-176B at a lower cost on cloud infrastructure.

Key takeaways

BLOOM-176B inference is 30% faster.
BLOOM-176B costs 1.2x less on AWS.
Optimization techniques included quantization and model pruning.

HHugging Face Blog#inference-optimization #model-optimization #cloud-deployment