fblgit/una-xaberius-34b-v1beta

Model Card for una-xaberius-34b-v1-beta (UNA: Uniform Neural Alignment)

This is another King-Breed from Juanako.AI

We have Identified some Problems with regular Quants use these models to play with Xaberius-34B and harness its power in full. Unfortunately we were not able to use any of TheBloke models, seems there is some undesired results out of it.

Introducing THE MODEL: XABERIUS 34B v1-BETA an experimental 34B LLaMa-Yi-34B based model, best on it's series. Trained on SFT, DPO and UNA (Unified Neural Alignment) on multiple datasets.

Timeline:

• 05-Dec-2023 v1-beta released
• 08-Dec-2023 Evaluation been "RUNNING" for 2 days.. no results yet
• 09-Dec-2023 Evaluation been "FINISHED", confirming #1 spot outperforming the contaminated-disqualified tigerbot :)

Results Here

Sidenote: Tests took 19H to run, wonder what happened in the 48H that HF held this one.. interim releasing manually other results??..

Model	Average	ARC (25-s)	HellaSwag (10-s)	MMLU (5-s)	TruthfulQA (MC) (0-s)	Winogrande (5-s)	GSM8K (5-s)
fblgit/una-cybertron-7b-v1-fp16	69.49	68.43	85.85	63.34	63.28	80.90	55.12
fblgit/una-cybertron-7b-v2-bf16	69.67	68.26	85.?4	63.23	64.63	81.37	55.04
fblgit/una-xaberius-34b-v1beta	74.18	70.39	86.77	78.15	61.45	84.93	63.38

Evaluations

• Scores 74.21 Outperforming former leader tigerbot-70b-chat and landing on #1 position of HuggingFace LeaderBoard: 08 December 2023.
• Scores 79.13 in MMLU, setting a new record not just for 34B but also for all OpenSource LLM's :)

SideNote: MMLU was a very solid 79+ .. weird, we'll dive further on this for irregularities :)

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
• When will be released the code and paper? When have time, contribute and it'll be faster.

Model Description

• Developed by: juanako.ai
• Author: Xavier M.
• Investors CONTACT HERE
• Model type: LLaMa YI-34B
• 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：

Framework versions

• Transformers 4.35.2-UNA
• Pytorch 2.1.0
• Datasets 2.14.6
• Tokenizers 0.14.1

Citations

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

@misc{unaxaberius34b,
  title={Xaberius 34B: Uniform Neural Alignment}, 
  author={Xavier Murias},
  year={2023},
  publisher = {HuggingFace},
  journal = {HuggingFace repository},
  howpublished = {\url{https://huggingface.co./fblgit/una-xaberius-34b-v1beta}},
}

Thanks to LoneStriker for his ExLLama2 models of high quality that works properly. Enormous Ku2 to Yi-34b Team for the outstanding model, UNA is only as good as its pre-trained model THANK YOU!

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	74.18
AI2 Reasoning Challenge (25-Shot)	70.39
HellaSwag (10-Shot)	86.77
MMLU (5-Shot)	78.15
TruthfulQA (0-shot)	61.45
Winogrande (5-shot)	84.93
GSM8k (5-shot)	63.38