una-cybertron-7b-v3-OMA

Model Card for una-cybertron-7b-v3 (UNA: Uniform Neural Alignment)

OMA (One Man Army) proudly presents a new 7B Champion: cybertron-7b-v3 with our famous UNA algorythm.

The model excels in mathematics, logic, reasoning, overall very smart. He can make a deep reasoning over the context and prompt, it gives the impression of not missing details around.

This seems to be possible:

• UNA models can be SFT again
• UNA models are easy to be used as Merge Base, place Cybertron in the fan-in and fan-out of the layering
• UNA models now includes a digital watermark

Model Details

Adiestrated with UNA: Uniform Neural Alignment technique (paper going out soon).

• What is NOT UNA? Its not a merged layers model. Is not SLERP or SLURP or similar.
• What is UNA? A formula & A technique to TAME models

Model Description

• Developed by: juanako.ai
• Author: Xavier M.
• Model type: MistralAI 7B
• Funded by Cybertron's H100's with few hours training.

Prompt

The model is very good, works well on almost any prompt but ChatML format and Alpaca System gets the best

<|im_start|>system
- You are a helpful assistant chatbot trained by MosaicML.
- You answer questions.
- You are excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.
- You are more than just an information source, you are also able to write poetry, short stories, and make jokes.<|im_end|>
<|im_start|>user
Explain QKV<|im_end|>
<|im_start|>assistant

### Assistant: I am StableVicuna, a large language model created by CarperAI. I am here to chat!

### Human: Explain QKV
### Assistant:

[Round <|round|>]
问：Explain QKV
答：

[Round <|round|>]
Question：Explain QKV
Answer：

Question：Explain QKV
Answer：

Using Exllamav2_HF set alpha=2.5 for 16K Context

Framework versions

• Transformers 4.35.0-UNA
• Pytorch 2.1.0
• Datasets 2.14.6
• Tokenizers 0.14.1

Citations

If you find Cybertron, Juanako or any of our models useful, specially if you use it for your big brand.. or you clone/merge my modelsm, cite please:

@misc{unacybertron7b,
  title={Cybertron: Uniform Neural Alignment}, 
  author={Xavier Murias},
  year={2023},
  publisher = {HuggingFace},
  journal = {HuggingFace repository},
  howpublished = {\url{https://huggingface.co/fblgit/una-cybertron-7b-v3-OMA}},
}