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|>]
้—ฎ๏ผšExplain QKV
็ญ”๏ผš
[Round <|round|>]
Question๏ผšExplain QKV
Answer๏ผš
Question๏ผšExplain QKV
Answer๏ผš

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}},
}
Downloads last month
770
Safetensors
Model size
7.24B params
Tensor type
FP16
ยท
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for fblgit/una-cybertron-7b-v3-OMA

Quantizations
4 models

Dataset used to train fblgit/una-cybertron-7b-v3-OMA

Spaces using fblgit/una-cybertron-7b-v3-OMA 24

Collection including fblgit/una-cybertron-7b-v3-OMA