File size: 2,291 Bytes
ef2b6fe db0e615 ef2b6fe db0e615 ef2b6fe |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 |
---
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 Mixtral-8x7B-v0.1-Instruct as a base.
### Models Merged
The following models were included in the merge:
* migtissera_Tess-2.0-Mixtral-8x7B-v0.2
* rombodawg_Open_Gpt4_8x7B_v0.2
* 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
```
|