Two new models: Arcee-Spark and Arcee-Agent
Two new Arcee.ai model videos for you today 😀 As usual, notebooks are available. Have fun testing these models, and don’t forget to follow Arcee.ai to stay on top of the latest Small Language Model action!
Arcee-Spark is an 8-billion parameter model created by Arcee.ai from Llama-3.1 8B. Spark outperforms its base model on many language and math benchmarks. In the video, I first run a quantized version locally. Then, I deploy the model on Amazon Web Services (AWS) with Amazon SageMaker. I run both synchronous and streaming inference. I also show you how to use the OpenAI Messages API, allowing you to invoke the model with the OpenAI prompting format and minimizing the migration cost. Finally, I compare ChatGPT and Arcee-Spark, and explain the benefits of open-source SLMs like Arcee-Spark compared to closed models.
Arcee-Agent is a 7-billion parameter model created by Arcee.ai from Qwen2–7B. Arcee Agent is currently one of the top models for function calls and tool usage, outperforming several versions of GPT-3.5 and GPT-4o In the video, I build a financial agent able to invoke the Yahoo Finance API to answer questions on listed companies, such as “what’s the stock price?”, “who’s the CEO”, “what is this company doing?” and more.
