Hermes-2-Pro-Mistral-7B
Maintainer: NousResearch
464
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| Property | Value |
|---|---|
| Model Link | View on HuggingFace |
| API Spec | View on HuggingFace |
| Github Link | No Github link provided |
| Paper Link | No paper link provided |
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Model overview
The Hermes-2-Pro-Mistral-7B is an upgraded and retrained version of the Nous Hermes 2 model. It was developed by NousResearch and includes an updated and cleaned version of the OpenHermes 2.5 Dataset, as well as a newly introduced Function Calling and JSON Mode dataset. This new version of Hermes maintains its excellent general task and conversation capabilities, but also excels at Function Calling, JSON Structured Outputs, and has improved on several other metrics.
The Hermes-2-Pro-Mistral-7B model takes advantage of a special system prompt and multi-turn function calling structure with a new chatml role to make function calling reliable and easy to parse. It was developed in collaboration with interstellarninja and Fireworks.AI.
Model inputs and outputs
Inputs
- Natural language instructions and prompts
Outputs
- Natural language responses
- Structured JSON outputs
- Reliable function calls
Capabilities
The Hermes-2-Pro-Mistral-7B model has excellent general task and conversation capabilities, and also excels at function calling and producing structured JSON outputs. It scored 90% on a function calling evaluation and 84% on a structured JSON Output evaluation.
What can I use it for?
The Hermes-2-Pro-Mistral-7B model can be used for a variety of tasks, including general language understanding and generation, task completion, and structured data output. Its strong performance on function calling and JSON output makes it well-suited for applications that require reliable and interpretable machine-generated responses, such as chatbots, virtual assistants, and data processing pipelines.
Things to try
One interesting thing to try with the Hermes-2-Pro-Mistral-7B model is exploring its capabilities around function calling and structured JSON output. The model's specialized prompt and multi-turn format for these tasks could enable novel applications that combine natural language interaction with reliable programmatic control and data manipulation.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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