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Inversion: fast, reliable structured LLMs (rysana.com)

AI LLM structured inference Developer Experience innovation

Inversion is a family of structured language models designed to solve speed, reliability, and reasoning issues in traditional AI systems, achieving up to 100× faster speeds and significantly lower latency.
Main Points
- Inversion models are highly efficientInversion models achieve high speed and reliability in structured tasks with less overhead and latency.
- Dynamic acceleration of inferenceInverted inference process leverages compiled structures to dynamically adjust compute needs, leading to acceleration.
- Continuous improvement in model performanceNew model generations aim for further improvements in latency, reliability, and quality.
- Prioritizing developer experienceDeveloper experience focuses on ensuring outputs always match expected data types.
- Advances in processing and input handlingExperiments promise significant advancements in attention processing and input handling.
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Function Calling with Hermes-2-Pro-Mistral-7B (drchrislevy.github.io)

LLM Function Calling Hermes-2-Pro-Mistral-7B Python Tools Format Language Models APIs

The article introduces the concept of Function Calling with Hermes-2-Pro-Mistral-7B, a tool designed to simplify the process of defining functions and tools for use with language model APIs. Through detailed examples, it demonstrates how this tool can be utilized to enhance the efficiency and capabilities of language models in executing specific, predefined functions.
Main Points
- Function Calling CapabilitiesFirst we will define some functions/tools which the LLM will have access to. Here I use langchain to convert the Python functions into the tools format used by OpenAI. It’s much faster than writing those JSON objects by hand. Note that Hermes-2-Pro-Mistral-7B also uses this same format!
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