README.md

---
license: cc-by-4.0
language:
- en
tags:
- merge
- not-for-all-audiences
- nsfw
---

<div style="display: flex; justify-content: center; align-items: center">
  <img src="https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B/resolve/main/assets/cybermaid.png">
</div
>

<p align="center">
  <big><b>Top 1 RP Performer on MT-bench 🤪</b
></big>
</p>

<p align="center">
  <strong>Next Gen Silicon-Based RP Maid</strong>
</p>

## WTF is This?

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.

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:
* MT-Bench normally correlates well with real world model quality
* It was an Alpaca prompt model with high benches which meant I could try swapping out my Marcoroni frankenmerge used in my previous model.

**MT-Bench Average Turn**
| model              | score     | size
|--------------------|-----------|--------
| gpt-4              | 8.99      |  -
| *xDAN-L1-Chat-RL-v1* | 8.35      |  7b
| Starling-7B        | 8.09      |  7b
| Claude-2           | 8.06      |  -
| **Silicon-Maid**   | **7.96**  |  **7b**
| *Loyal-Macaroni-Maid*| 7.95      |  7b
| gpt-3.5-turbo      | 7.94      |  20b?
| Claude-1           | 7.90      |  -
| OpenChat-3.5       | 7.81      |  -
| vicuna-33b-v1.3    | 7.12      |  33b
| wizardlm-30b       | 7.01      |  30b
| Llama-2-70b-chat   | 6.86      |  70b

<img src="https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B/resolve/main/assets/fig-silicon-loyal.png">

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?

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!

### The Sauce

```
models: # Top-Loyal-Bruins-Maid-DARE-7B
  - model: mistralai/Mistral-7B-v0.1
    # no parameters necessary for base model
  - model: xDAN-AI/xDAN-L1-Chat-RL-v1
    parameters:
      weight: 0.4
      density: 0.8
  - model: chargoddard/loyal-piano-m7
    parameters:
      weight: 0.3
      density: 0.8
  - model: Undi95/Toppy-M-7B
    parameters:
      weight: 0.2
      density: 0.4
  - model: NeverSleep/Noromaid-7b-v0.2
    parameters:
      weight: 0.2
      density: 0.4
  - model: athirdpath/NSFW_DPO_vmgb-7b
    parameters:
      weight: 0.2
      density: 0.4
merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16
```

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)

### Prompt Template (Alpaca)
I found the best SillyTavern results from using the Noromaid template but please try other templates! Let me know if you find anything good.

SillyTavern config files: [Context](https://files.catbox.moe/ifmhai.json), [Instruct](https://files.catbox.moe/ttw1l9.json).

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!

```
Below is an instruction that describes a task. Write a response that appropriately completes the request.

### Instruction:
{prompt}

### Response:
```