---
base_model:
- mistralai/Mixtral-8x7B-v0.1
- mistralai/Mixtral-8x7B-Instruct-v0.1
- jondurbin/bagel-dpo-8x7b-v0.2
- cognitivecomputations/dolphin-2.7-mixtral-8x7b
- NeverSleep/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss
- ycros/BagelMIsteryTour-v2-8x7B
- smelborp/MixtralOrochi8x7B
library_name: transformers
tags:
- mergekit
- merge

---

yum yum GGUF quants in my tum :^) enjoy lmg and vali, original model card below

<hr>

# maid-yuzu-v8-alter

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

v7's approach worked better than I thought, so I tried something even weirder as a test. I don't think a proper model will come out, but I'm curious about the results.

## Merge Details
### Merge Method

This model was merged using the SLERP merge method.

This models were merged using the SLERP method in the following order:

    maid-yuzu-v8-base: mistralai/Mixtral-8x7B-v0.1 + mistralai/Mixtral-8x7B-Instruct-v0.1 = 0.5
    maid-yuzu-v8-step1: above + jondurbin/bagel-dpo-8x7b-v0.2 = 0.25
    maid-yuzu-v8-step2: above + cognitivecomputations/dolphin-2.7-mixtral-8x7b = 0.25
    maid-yuzu-v8-step3: above + NeverSleep/Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss = 0.25
    maid-yuzu-v8-step4-alter: above + ycros/BagelMIsteryTour-v2-8x7B = 0.5
    maid-yuzu-v8-alter: above + smelborp/MixtralOrochi8x7B = 0.5

### Models Merged

The following models were included in the merge:
* [smelborp/MixtralOrochi8x7B](https://huggingface.co/smelborp/MixtralOrochi8x7B)
* ../maid-yuzu-v8-step4-alter

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model:
  model:
    path: ../maid-yuzu-v8-step4-alter
dtype: bfloat16
merge_method: slerp
parameters:
  t:
  - value: 0.5
slices:
- sources:
  - layer_range: [0, 32]
    model:
      model:
        path: ../maid-yuzu-v8-step4-alter
  - layer_range: [0, 32]
    model:
      model:
        path: smelborp/MixtralOrochi8x7B
```