Athene-70B
Maintainer: Nexusflow
148
🏷️
| 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
Athene-70B is an open-source large language model developed by the Nexusflow team. It is based on the Llama-3-70B-Instruct model and is further trained using reinforcement learning with human feedback (RLHF) to achieve high performance on the Arena-Hard-Auto benchmark, a proxy for the Chatbot Arena.
Compared to other open-source and proprietary models, Athene-70B demonstrates strong performance on the Arena-Hard benchmark, scoring 77.8% compared to 79.2% for the proprietary GPT-4o model and 46.6% for the open-source Llama-3-70B model.
Model inputs and outputs
Inputs
Athene-70Btakes in text-based conversational prompts, similar to theLlama-3-70B-Instructmodel.
Outputs
- The model generates natural language text responses, aiming to be helpful, informative and engaging in conversations.
Capabilities
Athene-70B is a capable chat model that can handle a variety of conversational tasks. It has been trained to engage in natural dialogue, answer questions, and assist with various information-seeking and task-completion queries. The model demonstrates strong performance on benchmarks that measure a model's ability to provide helpful and relevant responses in a conversational setting.
What can I use it for?
Athene-70B could be a useful tool for developers and researchers working on conversational AI applications, such as virtual assistants, chatbots, and dialogue systems. The model's strong performance on the Arena-Hard benchmark suggests it may be particularly well-suited for building engaging and user-friendly chat interfaces.
Things to try
Developers could experiment with Athene-70B in a variety of conversational scenarios, such as customer service, task planning, open-ended discussions, and information lookup. The model's flexibility and strong performance make it an interesting candidate for further exploration and development.
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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