---
license: cc-by-nc-4.0
tags:
- conversational
- mixtral
- merge
- mergekit
---

<img src="https://files.catbox.moe/zdxyzv.png" width="400"/>

## TeTO-MS-8x7b

<b>Te</b>soro  + <b>T</b>yphon + <b>O</b>penGPT

Presenting a Model Stock experiment combining the unique strengths from the following 8x7b Mixtral models:
* Tess-2.0-Mixtral-8x7B-v0.2 / [migtissera](https://huggingface.co/migtissera) / General Purpose 
* Typhon-Mixtral-v1 / [Sao10K](https://huggingface.co/Sao10K) / Creative & Story Completion
* Open_Gpt4_8x7B_v0.2 / [rombodawg](https://huggingface.co/rombodawg) / Conversational

<H2>Methodology</H2>

> [I]nnovative layer-wise weight averaging technique surpasses state-of-the-art model methods such as Model Soup, utilizing only two fine-tuned models. This strategy can be aptly coined Model Stock, highlighting its reliance on selecting a minimal number of models to draw a more optimized-averaged model
<i> (From [arXiv:2403.19522](https://arxiv.org/pdf/2403.19522))</i>


* Methodology and merging process was based on the following paper - [Model Stock: All we need is just a few fine-tuned models](https://arxiv.org/abs/2403.19522)
* Initial model selection was based on top performing models of Mixtral architecture covering a variety of use cases and skills
* Base model (Mixtral Instruct 8x7b v0.1) was chosen after outperforming two other potential base models in terms of MMLU benchmark performance.

# Output

<img src="https://files.catbox.moe/bw97yg.PNG" width="400"/>

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using models/Mixtral-8x7B-v0.1-Instruct as a base.

### Models Merged

The following models were included in the merge:
* models/migtissera_Tess-2.0-Mixtral-8x7B-v0.2
* models/rombodawg_Open_Gpt4_8x7B_v0.2
* models/Sao10K_Typhon-Mixtral-v1

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: models/migtissera_Tess-2.0-Mixtral-8x7B-v0.2
  - model: models/Sao10K_Typhon-Mixtral-v1
  - model: models/rombodawg_Open_Gpt4_8x7B_v0.2 
merge_method: model_stock
base_model: models/Mixtral-8x7B-v0.1-Instruct
dtype: float16
```