Maintainer: fblgit

Total Score


Last updated 5/28/2024


Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Model overview

The una-cybertron-7b-v2-bf16 model, developed by juanako.ai and maintained by fblgit, is a 7 billion parameter AI model that uses the UNA (Uniform Neural Alignment) technique. It outperforms other 7B models, scoring #1 on the HuggingFace Open LLM Leaderboard with a score of 69.67. Similar models include the Mistral-7B-v0.1, Intel/neural-chat-7b-v3-2, perlthoughts/Chupacabra-7B-v2, and fblgit/una-cybertron-7b-v1-fp16.

Model inputs and outputs

The una-cybertron-7b-v2-bf16 model is a text-to-text AI model, meaning it takes text as input and generates text as output. It performs well on a variety of natural language tasks, including question answering, logical reasoning, and open-ended conversation.


  • Text prompts in natural language


  • Generated text responses in natural language


The una-cybertron-7b-v2-bf16 model excels at mathematical and logical reasoning, scoring highly on benchmarks such as the HuggingFace Open LLM Leaderboard. It can engage in deep contextual analysis and provide detailed, well-reasoned responses.

What can I use it for?

The una-cybertron-7b-v2-bf16 model could be used for a wide range of natural language processing tasks, such as:

  • Chatbots and conversational AI assistants
  • Question answering and information retrieval
  • Content generation for websites, blogs, or social media
  • Summarization and text analysis
  • Logical and mathematical problem-solving

Things to try

One interesting aspect of the una-cybertron-7b-v2-bf16 model is its use of the UNA (Uniform Neural Alignment) technique, which the maintainer claims helps "tame" the model. Experimenting with different prompts and tasks could reveal insights into how this technique affects the model's behavior and capabilities.

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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