Nous-Hermes-2-SOLAR-10.7B
Maintainer: NousResearch
196
🏋️
| 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 Nous-Hermes-2-SOLAR-10.7B is the flagship Nous Research model on the SOLAR 10.7B base model. It was trained on 1,000,000 entries of primarily GPT-4 generated data, as well as other high quality data from open datasets across the AI landscape. This model is a significant improvement over the base SOLAR 10.7B model and approaches the performance of the Nous-Hermes-2-Yi-34B model across a variety of benchmarks.
Model inputs and outputs
The Nous-Hermes-2-SOLAR-10.7B model uses the ChatML prompt format, which allows for more structured multi-turn dialogue with the AI. This format enables OpenAI endpoint compatibility, and people familiar with the ChatGPT API will find the format familiar.
Inputs
- Prompts following the ChatML format, with special tokens denoting the start and end of turns, as well as the roles of the participants.
Outputs
- Coherent, contextually appropriate responses generated by the model based on the provided prompts.
Capabilities
The Nous-Hermes-2-SOLAR-10.7B model has demonstrated strong performance across a variety of benchmarks, including GPT4All, AGIEval, BigBench, and TruthfulQA. It excels at tasks like question answering, logical reasoning, and following complex instructions.
What can I use it for?
The Nous-Hermes-2-SOLAR-10.7B model can be used for a wide range of language tasks, from generating creative text to understanding and following complex instructions. It could be particularly useful for building conversational AI applications, like chatbots or virtual assistants, that require more structured and contextual interactions.
Things to try
One interesting aspect of the Nous-Hermes-2-SOLAR-10.7B model is its use of the ChatML prompt format. This allows for more sophisticated multi-turn dialogues, where the model can maintain context and coherence across multiple exchanges. Developers could experiment with building applications that leverage this capability, such as task-oriented chatbots or interactive writing assistants.
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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