One major challenge we've observed with current human-computer interactions is that many simple, one-step tasks become unnecessarily complex, multi-step workflows due to limitations of current GUIs. AI agents can solve this, but existing AI agent models are slow and costly.
To tackle these issues, we built lightweight AI agent models based on our Octopus V2, small language models for function calling (You can learn more about our functional token approach in our paper: https://huggingface.co/papers/2404.01744). These models support developers in building AI agents both on-device and in the cloud. Our function calling models are 4 times faster, 10 times cheaper, and more accurate than GPT-4o.
We’d love for you to try out our model APIs and see the difference for yourself. Your feedback and thoughts are incredibly valuable to us, and we’re here to answer any questions you might have.
Links:
Website: https://www.nexa4ai.com/octoverse
Playground: https://hub.nexa4ai.com
Documentation: https://docs.nexa4ai.com/
Join Discord to discuss: https://discord.com/invite/thRu2HaK4D
Paper: https://huggingface.co/papers/2404.01744
Show HN: Use functional tokens for AI agents to simplify app workflows
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