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--- |
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license: cc-by-nc-4.0 |
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tags: |
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- conversational |
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- mixtral |
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- merge |
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- mergekit |
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--- |
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<img src="https://files.catbox.moe/zdxyzv.png" width="400"/> |
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## TeTO-MS-8x7b |
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<b>Te</b>soro + <b>T</b>yphon + <b>O</b>penGPT |
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Presenting a Model Stock experiment combining the unique strengths from the following 8x7b Mixtral models: |
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* Tess-2.0-Mixtral-8x7B-v0.2 / [migtissera](https://huggingface.co/migtissera) / General Purpose |
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* Typhon-Mixtral-v1 / [Sao10K](https://huggingface.co/Sao10K) / Creative & Story Completion |
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* Open_Gpt4_8x7B_v0.2 / [rombodawg](https://huggingface.co/rombodawg) / Conversational |
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<H2>Methodology</H2> |
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> [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 |
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<i> (From [arXiv:2403.19522](https://arxiv.org/pdf/2403.19522))</i> |
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* 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) |
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* Initial model selection was based on top performing models of Mixtral architecture covering a variety of use cases and skills |
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* Base model (Mixtral Instruct 8x7b v0.1) was chosen after outperforming two other potential base models in terms of MMLU benchmark performance. |
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# Output |
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<img src="https://files.catbox.moe/bw97yg.PNG" width="400"/> |
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). |
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## Merge Details |
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### Merge Method |
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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. |
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### Models Merged |
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The following models were included in the merge: |
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* migtissera_Tess-2.0-Mixtral-8x7B-v0.2 |
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* rombodawg_Open_Gpt4_8x7B_v0.2 |
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* Sao10K_Typhon-Mixtral-v1 |
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### Configuration |
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The following YAML configuration was used to produce this model: |
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```yaml |
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models: |
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- model: models/migtissera_Tess-2.0-Mixtral-8x7B-v0.2 |
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- model: models/Sao10K_Typhon-Mixtral-v1 |
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- model: models/rombodawg_Open_Gpt4_8x7B_v0.2 |
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merge_method: model_stock |
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base_model: models/Mixtral-8x7B-v0.1-Instruct |
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dtype: float16 |
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``` |
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