una-cybertron-7b-v2-bf16/README.md

license, library_name, tags, datasets, model-index

license	library_name	tags	datasets	model-index
apache-2.0	transformers	juanako UNA cybertron fbl	fblgit/tree-of-knowledge Open-Orca/SlimOrca-Dedup allenai/ultrafeedback_binarized_cleaned	name results una-cybertron-7b-v2-bf16 task dataset metrics source type name text-generation Text Generation name type config split args AI2 Reasoning Challenge (25-Shot) ai2_arc ARC-Challenge test num_few_shot 25 type value name acc_norm 68.26 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/una-cybertron-7b-v2-bf16 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type split args HellaSwag (10-Shot) hellaswag validation num_few_shot 10 type value name acc_norm 85.85 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/una-cybertron-7b-v2-bf16 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args MMLU (5-Shot) cais/mmlu all test num_few_shot 5 type value name acc 63.23 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/una-cybertron-7b-v2-bf16 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args TruthfulQA (0-shot) truthful_qa multiple_choice validation num_few_shot 0 type value mc2 64.63 url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/una-cybertron-7b-v2-bf16 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args Winogrande (5-shot) winogrande winogrande_xl validation num_few_shot 5 type value name acc 80.98 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/una-cybertron-7b-v2-bf16 Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args GSM8k (5-shot) gsm8k main test num_few_shot 5 type value name acc 55.04 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=fblgit/una-cybertron-7b-v2-bf16 Open LLM Leaderboard

Model Card for una-cybertron-7b-v2-bf16 (UNA: Uniform Neural Alignment)

We strike back, introducing Cybertron 7B v2 a 7B MistralAI based model, best on it's series. Trained on SFT, DPO and UNA (Unified Neural Alignment) on multiple datasets. He scores EXACTLY #1 with 69.67+ score on HF LeaderBoard board, #8 ALL SIZES top score.

• v1 Scoring #1 at 2 December 2023 with 69.43 ..few models were releasse .. but only 1 can survive: CYBERTRON!
• v2 Scoring #1 at 5 December 2023 with 69.67

Model	Average	ARC (25-s)	HellaSwag (10-s)	MMLU (5-s)	TruthfulQA (MC) (0-s)	Winogrande (5-s)	GSM8K (5-s)
mistralai/Mistral-7B-v0.1	60.97	59.98	83.31	64.16	42.15	78.37	37.83
Intel/neural-chat-7b-v3-2	68.29	67.49	83.92	63.55	59.68	79.95	55.12
perlthoughts/Chupacabra-7B-v2	63.54	66.47	85.17	64.49	57.6	79.16	28.35
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

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.

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: 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

Users also report that exllamav2_HF loader, 8bpw-h8 exl2 quant, simple-1 preset provides good results

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-v2-bf16}},
}

Special thanks to @TheBloke & @bartowski for converting the models and their support to the community. Thank you!

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	69.67
AI2 Reasoning Challenge (25-Shot)	68.26
HellaSwag (10-Shot)	85.85
MMLU (5-Shot)	63.23
TruthfulQA (0-shot)	64.63
Winogrande (5-shot)	80.98
GSM8k (5-shot)	55.04