How to run Llama 3 with AIME API to Deploy Conversational AI Solutions
With LLaMa 3 you get a collection of pretrained state-of-the-art large language models for free. Unlike the well-known ChatGPT, LLaMa models are downloadable and compatible with existing hardware for execution.
In our previous articles about the Llama models (Llama 2, Llama 1), we delved into the details of running Llama as console application as well as deploying it via the AIME API Server. Embracing the next step with Llama 3, the most recent advancement in the realm of open large language models, we will now provide a comprehensive guide on how to set up Llama 3 and operate it with the AIME API server, opening up new possibilities for delivering AI conversational experiences.
At AIME, we understand the importance of providing AI tools as services to harness the full potential of technologies like Llama. That's why we're excited to announce the integration of Llama 3 with our new AIME-API as one of the first providers, offering developers a streamlined solution for delivering its capabilities as a scalable HTTP/HTTPS service for easy integration with client applications. Whether you're building chatbots, virtual assistants, or interactive customer support systems, this integration offers flexibility to make modifications and adjustments to the model and the scalability to deploy such solutions.
As you may already know, there are two previous versions of the Llama model - so what is the advantage of Llama 3 over the older versions?
