The DeepSeek-R1 model has taken the AI world by storm, showcasing reasoning skills on par with OpenAI's models while being significantly more cost-efficient. This model provides step-by-step responses, mimicking human thought processes to solve problems in science, mathematics, coding, and general knowledge.
What Makes DeepSeek-R1 Special?
DeepSeek-R1 was developed to address the limitations of its predecessor, DeepSeek-R1-Zero, which struggled with repetition, poor readability, and language mixing. By incorporating two stages of reinforcement learning (RL) and two stages of supervised fine-tuning (SFT), DeepSeek-R1 achieves human-like reasoning patterns and robust performance.
Accessible and Efficient
Available on the Hugging Face hub, DeepSeek-R1 and its distilled versions, such as DeepSeek-R1-Distill, are fine-tuned on open-source models like Meta's Llama and Alibaba Cloud's Qwen. These models can be easily deployed using Amazon Web Services (AWS) and the Open Platform for Enterprise AI (OPEA) ChatQnA example. Researchers with limited computing power can now run these models cost-effectively. According to Mario Krenn, leader of the Artificial Scientist Lab at the Max Planck Institute for the Science of Light in Erlangen, Germany, “an experiment that cost $370 to run with o1, cost less than $10 with R1.”
OPEA: Simplifying GenAI Development
OPEA, a Linux Foundation project, provides an open-source framework of microservices to simplify the development, production, and adoption of generative AI (GenAI) applications. With OPEA, you can leverage the expertise of about 50 partners to build your application without starting from scratch.
Get Started Quickly
Running an LLM can be as simple as setting up and deploying the ChatQnA example with Docker. The default LLM is meta-llama/Meta-Llama-3-8B-Instruct, but you can easily switch to any DeepSeek-R1-Distill model by changing one environment variable.
Why Choose DeepSeek-R1-Distill Models?
These smaller models are more feasible for enterprises, requiring less memory and power. Using Intel® Xeon® processors, you can get DeepSeek-R1-Distill models running in minutes without writing new code. OPEA enables you to build on and customize these models to suit your GenAI application’s needs.
Learn More
After setting up, you can further enhance performance by using larger AWS instances or multiple nodes, experimenting with different DeepSeek-R1-Distill models, and exploring other GenAI examples from OPEA.
Ready to learn more? Check out the full technical article.
