OpenHermes-13B
Maintainer: teknium
53
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| Property | Value |
|---|---|
| Run this model | Run 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
OpenHermes-13B is a large language model (LLM) developed by teknium that has been fine-tuned on over 242,000 entries of primarily GPT-4 generated data. This includes datasets from sources like GPTeacher, WizardLM, Airoboros GPT-4, Camel-AI, CodeAlpaca, and more. The model was trained to excel at a variety of language tasks, from text generation to following complex instructions.
One key difference between OpenHermes-13B and similar models like OpenHermes-2.5-Mistral-7B is the fully open-source nature of its training dataset. This allows for greater transparency and opportunities for further research and development.
Model inputs and outputs
Inputs
- Natural language prompts and instructions covering a wide range of topics and tasks
Outputs
- Coherent, context-aware responses in natural language
- Completion of complex tasks and instructions
- Generation of creative and informative text
Capabilities
OpenHermes-13B demonstrates impressive capabilities across a variety of benchmarks, including strong performance on the GPT4All, AGIEval, and BigBench test suites. The model is particularly adept at following instructions, understanding context, and generating high-quality text.
What can I use it for?
With its broad knowledge and flexible language understanding, OpenHermes-13B can be useful for a wide range of applications, such as:
- Chatbots and virtual assistants
- Content generation (e.g., articles, stories, scripts)
- Task completion and instruction following
- Question answering and knowledge retrieval
- Educational and research applications
Things to try
One interesting aspect of OpenHermes-13B is its ability to engage in multi-turn dialogues and roleplay scenarios, as demonstrated by the example outputs. This could be an area to further explore, such as by creating interactive chatbots or virtual characters.
Additionally, the model's strong performance on benchmarks related to reasoning, logical deduction, and understanding of complex concepts suggests potential applications in fields like education, scientific research, and problem-solving.
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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