Top 1 RP Performer on MT-bench 🤪

Next Gen Silicon-Based RP Maid

## 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. Quants can be found [here](https://huggingface.co/collections/SanjiWatsuki/silicon-maid-7b-658d1669292816fe4992daa4). 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* | 8.24^1 | 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 ^1 xDAN's testing placed it 8.35 - this number is from my independent MT-Bench run.

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 a lot of Reasoning and Coding skills in the merger. This was a much greater MT-Bench dropoff than I expected, perhaps suggesting the Math/Reasoning 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: ``` ### Other Benchmarks | Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench | |---|---:|---:|---:|---:|---:| | [OpenPipe/mistral-ft-optimized-1218](https://huggingface.co/OpenPipe/mistral-ft-optimized-1218) [📄](https://gist.github.com/mlabonne/36c412889c4acfad7061f269a31f9055) | 56.85 | 44.74 | 75.6 | 59.89 | 47.17 | | [**Silicon-Maid-7B**](https://huggingface.co/SanjiWatsuki/Silicon-Maid-7B) [📄](https://gist.github.com/DHNishi/315ba1abba27af930f5f546af3515735) | **56.45**| 44.74| 74.26| 61.5| 45.32| | [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B) [📄](https://gist.github.com/mlabonne/14687f1eb3425b166db511f31f8e66f6) | 53.51 | 43.67 | 73.24 | 55.37 | 41.76 | | [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) [📄](https://gist.github.com/mlabonne/88b21dd9698ffed75d6163ebdc2f6cc8) | 52.42 | 42.75 | 72.99 | 52.99 | 40.94 | | [openchat/openchat_3.5](https://huggingface.co/openchat/openchat_3.5) [📄](https://gist.github.com/mlabonne/e23d7d8418619cf5b1ca10da391ac629) | 51.34 | 42.67 | 72.92 | 47.27 | 42.51 | | [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha) [📄](https://gist.github.com/mlabonne/c31cc46169ef3004c0df250017d5cac9) | 51.16 | 42.06 | 72.72 | 47.33 | 42.53 | | [HuggingFaceH4/zephyr-7b-beta](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta) [📄](https://gist.github.com/mlabonne/32a36f448fd36a3100c325d51d01c0a1) | 50.99 | 37.33 | 71.83 | 55.1 | 39.7 |