Sonya 7B

🚀 Sonya-7B

Sonya-7B is currently the #1 model in the first turn of MT-Bench, outperforming GPT-4, and ranks #2 overall in MT-Bench. It serves as a versatile model suitable for various tasks, such as assistant services and role - playing.

🚀 Quick Start

Based on the parent models, this model is expected to be used with an 8192 context window. You can experimentally try a 16384 context by using NTK scaling alpha of 2.6.

✨ Features

Outstanding Performance

Sonya-7B significantly outperforms its parent models on MT - Bench. In the MT - Bench average turn, it scores 8.52, trailing only behind GPT - 4.

Model Composition

It's a merge of [xDAN - AI/xDAN - L1 - Chat - RL - v1](https://huggingface.co/xDAN - AI/xDAN - L1 - Chat - RL - v1), [Jan - Ai's Stealth v1.2](https://huggingface.co/jan - hq/stealth - v1.2), [chargoddard/piano - medley - 7b](https://huggingface.co/chargoddard/piano - medley - 7b), [NeverSleep/Noromaid - 7B - v0.2](https://huggingface.co/NeverSleep/Noromaid - 7b - v0.2), and [athirdpath/NSFW_DPO_vmgb - 7b](athirdpath/NSFW_DPO_vmgb - 7b).

Selection Rationale

• MT - Bench Correlation: MT - Bench is usually well - correlated with real - world model quality, and xDAN performs well on it.
• Prompt Consistency: Most models in the mix use Alpaca prompt formatting, ensuring prompt consistency.
• Magic Ingredient: Stealth v1.2 seems to boost MT - Bench scores.
• RP Enhancement: Adding RP models improves performance in Writing and Role - play benchmarks.

Other Benchmark Results

First turn

Second turn

📚 Documentation

The Sauce

models:
  - model: xDAN-AI/xDAN-L1-Chat-RL-v1
    parameters:
      weight: 1
      density: 1
  - model: chargoddard/piano-medley-7b
    parameters:
      weight: 0.3
  - model: jan-hq/stealth-v1.2
    parameters:
      weight: 0.2
  - model: NeverSleep/Noromaid-7b-v0.2
    parameters:
      weight: 0.2
  - model: athirdpath/NSFW_DPO_vmgb-7b
    parameters:
      weight: 0.2
merge_method: ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  density: 0.4
  int8_mask: true
  normalize: true
dtype: bfloat16

Note: There was no additional training, finetuning, or DPO. This is a straight merger.

Prompt Template (Alpaca)

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

### Instruction:
{prompt}

### Response:

It's found that this model performed worse with the xDAN prompt format. So, despite the heavy weight of xDAN in this merger, it's recommended against its use.

Replication of MT - Bench Run

If you want to replicate the MT - Bench run, make sure to apply the Alpaca prompt template to the model. You can do this by putting "alpaca" in the model path to trigger the AlpacaAdapter.

📄 License

This project is licensed under the CC - BY - 4.0 license.