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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ datasets:
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+ - fblgit/tree-of-knowledge
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+ - Open-Orca/SlimOrca-Dedup
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+ - allenai/ultrafeedback_binarized_cleaned
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+ library_name: transformers
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+ tags:
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+ - juanako
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+ - UNA
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+ - cybertron
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+ - fbl
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+ ---
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+
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+ # Model Card for una-cybertron-7b-v2-bf16 (UNA: Uniform Neural Alignment)
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+
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+ 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.
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+ He scores [EXACTLY](https://huggingface.co/datasets/open-llm-leaderboard/details_fblgit__una-cybertron-7b-v2-bf16) **#1** with **69.67**+ score on HF LeaderBoard board, **#8** ALL SIZES top score.
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+
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+ * v1 Scoring **#1** at 2 December 2023 with 69.43 ..few models were releasse .. but only 1 can survive: CYBERRTON!
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+ * v2 Scoring **#1** at 5 December 2023 with 69.67
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+ 2
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+
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+ | Model | Average | ARC (25-s) | HellaSwag (10-s) | MMLU (5-s) | TruthfulQA (MC) (0-s) | Winogrande (5-s) | GSM8K (5-s) |
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+ | --- | --- | --- | --- | --- | --- | --- | --- |
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+ | [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) | 60.97 | 59.98 | 83.31 | 64.16 | 42.15 | 78.37 | 37.83 |
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+ | [Intel/neural-chat-7b-v3-2](https://huggingface.co/Intel/neural-chat-7b-v3-2) | 68.29 | 67.49 | 83.92 | 63.55 | 59.68 | 79.95 | 55.12 |
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+ | [perlthoughts/Chupacabra-7B-v2](https://huggingface.co/perlthoughts/Chupacabra-7B-v2) | 63.54 | 66.47 | 85.17 | 64.49 | 57.6 | 79.16 | 28.35 |
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+ | [fblgit/una-cybertron-7b-v1-fp16](https://huggingface.co/fblgit/una-cybertron-7b-v1-fp16) | **69.49** | **68.43** | **85.85** | 63.34 | **63.28** | **80.90** | **55.12** |
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+ | [fblgit/una-cybertron-7b-v2-bf16](https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16) | **69.67** | **68.26** | **85.?4** | 63.23 | **64.63** | **81.37** | **55.04** |
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+
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+ The model excels in mathematics, logic, reasoning, overall very smart.
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+
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+ ## Model Details
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+
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+ Adiestrated with UNA: Uniform Neural Alignment technique (paper going out soon).
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+ * What is **NOT** UNA? Its not a merged layers model. Is not SLERP or SLURP or similar.
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+ * What **is** UNA? A formula & A technique to *TAME* models
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+ * When will be released the code and paper? When have time, contribute and it'll be faster.
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+
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+ ### Model Description
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+
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+ - **Developed by:** [juanako.ai](https://juanako.ai)
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+ - **Author:** [Xavier M.](xavi@juanako.ai)
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+ - **Investors** [CONTACT HERE](billing@juanako.ai)
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+ - **Model type:** MistralAI 7B
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+ - **Funded by Cybertron's H100's** with few hours training.
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+
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+ ### Prompt
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+ The model is very good, works well on almost any prompt but ChatML format and Alpaca System gets the best
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+ ```
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+ <|im_start|>system
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+ - You are a helpful assistant chatbot trained by MosaicML.
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+ - You answer questions.
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+ - You are excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.
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+ - You are more than just an information source, you are also able to write poetry, short stories, and make jokes.<|im_end|>
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+ <|im_start|>user
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+ Explain QKV<|im_end|>
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+ <|im_start|>assistant
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+ ```
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+ ```
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+ ### Assistant: I am StableVicuna, a large language model created by CarperAI. I am here to chat!
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+
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+ ### Human: Explain QKV
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+ ### Assistant:
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+ ```
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+ ```
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+ [Round <|round|>]
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+ 问:Explain QKV
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+ 答:
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+ ```
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+ ```
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+ [Round <|round|>]
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+ Question:Explain QKV
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+ Answer:
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+ ```
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+ ```
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+ Question:Explain QKV
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+ Answer:
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+ ```
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.0-UNA
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+ - Pytorch 2.1.0
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+
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+ ### Citations
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+ 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:
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+ ```
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+ @misc{unacybertron7b,
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+ title={Cybertron: Uniform Neural Alignment},
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+ author={Xavier Murias},
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+ year={2023},
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+ publisher = {HuggingFace},
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+ journal = {HuggingFace repository},
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+ howpublished = {\url{https://huggingface.co/fblgit/una-cybertron-7b-v2-bf16}},
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+ }
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+ ```
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+
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+ Special thanks to @TheBloke & @bartowski for converting the models and their support to the community. Thank you!
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+ "vocab_size": 32000
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+ }
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