SanjiWatsuki
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README.md
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license: cc-by-
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---
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license: cc-by-4.0
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language:
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- en
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tags:
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- merge
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- not-for-all-audiences
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- nsfw
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<div style="display: flex; justify-content: center; align-items: center">
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<img src="https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B/resolve/main/assets/cybermaid.png">
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</div
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>
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<p align="center">
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<big><b>Top 1 RP Performer on MT-bench 🤪</b
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></big>
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</p>
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<p align="center">
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<strong>Next Gen Silicon-Based RP Maid</strong>
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</p>
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## WTF is This?
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Silicon-Maid-7B is another model targeted at being both strong at RP **and** being a smart cookie that can follow character cards very well. As of right now, Silicon-Maid-7B outscores both of my previous 7B RP models in my RP benchmark and I have been impressed by this model's creativity. It is suitable for RP/ERP and general use.
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It's built on [xDAN-AI/xDAN-L1-Chat-RL-v1](https://huggingface.co/xDAN-AI/xDAN-L1-Chat-RL-v1), a 7B model which scores unusually high on MT-Bench, and chargoddard/loyal-piano-m7, an Alpaca format 7B model with surprisingly creative outputs. I was excited to see this model for two main reasons:
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* MT-Bench normally correlates well with real world model quality
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* It was an Alpaca prompt model with high benches which meant I could try swapping out my Marcoroni frankenmerge used in my previous model.
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**MT-Bench Average Turn**
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| model | score | size
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|--------------------|-----------|--------
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| gpt-4 | 8.99 | -
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| *xDAN-L1-Chat-RL-v1* | 8.35 | 7b
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| Starling-7B | 8.09 | 7b
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| Claude-2 | 8.06 | -
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| **Silicon-Maid** | **7.96** | **7b**
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| *Loyal-Macaroni-Maid*| 7.95 | 7b
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| gpt-3.5-turbo | 7.94 | 20b?
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| Claude-1 | 7.90 | -
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| OpenChat-3.5 | 7.81 | -
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| vicuna-33b-v1.3 | 7.12 | 33b
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| wizardlm-30b | 7.01 | 30b
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| Llama-2-70b-chat | 6.86 | 70b
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<img src="https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B/resolve/main/assets/fig-silicon-loyal.png">
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It's unclear to me if xDAN-L1-Chat-RL-v1 is overtly benchmaxxing but it seemed like a solid 7B from my limited testing (although nothing that screams 2nd best model behind GPT-4). Amusingly, the model lost almost all of its coding and math ability in the merge but somehow *improved* in "Extraction". This was a much greater MT-Bench dropoff than I expected, perhaps suggesting the Math/Coding ability in the original model was rather dense and susceptible to being lost to a DARE TIE merger?
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Besides that, the merger is almost identical to the Loyal-Macaroni-Maid merger with a new base "smart cookie" model. If you liked any of my previous RP models, give this one a shot and let me know in the Community tab what you think!
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### The Sauce
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```
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models: # Top-Loyal-Bruins-Maid-DARE-7B
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- model: mistralai/Mistral-7B-v0.1
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# no parameters necessary for base model
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- model: xDAN-AI/xDAN-L1-Chat-RL-v1
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parameters:
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weight: 0.4
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density: 0.8
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- model: chargoddard/loyal-piano-m7
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parameters:
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weight: 0.3
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density: 0.8
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- model: Undi95/Toppy-M-7B
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parameters:
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weight: 0.2
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density: 0.4
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- model: NeverSleep/Noromaid-7b-v0.2
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parameters:
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weight: 0.2
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density: 0.4
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- model: athirdpath/NSFW_DPO_vmgb-7b
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parameters:
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weight: 0.2
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density: 0.4
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merge_method: dare_ties
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base_model: mistralai/Mistral-7B-v0.1
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parameters:
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int8_mask: true
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dtype: bfloat16
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```
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For more information about why I use this merger, see the [Loyal-Macaroni-Maid repo](https://huggingface.co/SanjiWatsuki/Loyal-Macaroni-Maid-7B#the-sauce-all-you-need-is-dare)
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### Prompt Template (Alpaca)
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I found the best SillyTavern results from using the Noromaid template but please try other templates! Let me know if you find anything good.
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SillyTavern config files: [Context](https://files.catbox.moe/ifmhai.json), [Instruct](https://files.catbox.moe/ttw1l9.json).
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Additionally, here is my highly recommended [Text Completion preset](https://huggingface.co/SanjiWatsuki/Loyal-Macaroni-Maid-7B/blob/main/Characters/MinP.json). You can tweak this by adjusting temperature up or dropping min p to boost creativity or raise min p to increase stability. You shouldn't need to touch anything else!
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```
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Below is an instruction that describes a task. Write a response that appropriately completes the request.
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### Instruction:
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{prompt}
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### Response:
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```
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