transformers safetensors mixtral text-generation mergekit merge arxiv:2311.03099 arxiv:2306.01708 base_model:cognitivecomputations/dolphin-2.7-mixtral-8x7b base_model:Sao10K/Sensualize-Mixtral-bf16 base_model:jondurbin/bagel-dpo-8x7b-v0.2 base_model:mistralai/Mixtral-8x7B-v0.1 base_model:Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora base_model:smelborp/MixtralOrochi8x7B autotrain_compatible endpoints_compatible text-generation-inference region:us
---
base_model:
- cognitivecomputations/dolphin-2.7-mixtral-8x7b
- Sao10K/Sensualize-Mixtral-bf16
- jondurbin/bagel-dpo-8x7b-v0.2
- mistralai/Mixtral-8x7B-v0.1
- Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora
- smelborp/MixtralOrochi8x7B
- mistralai/Mixtral-8x7B-v0.1
library_name: transformers
tags:
- mergekit
- merge

---
# maid-yuzu-v4

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

This model is a model that I merged with several models I know because I had leftover credits for merging. Of course, the results are not good. Please do not use it.

## Merge Details
### Merge Method

This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) as a base.

### Models Merged

The following models were included in the merge:
* [cognitivecomputations/dolphin-2.7-mixtral-8x7b](https://huggingface.co/cognitivecomputations/dolphin-2.7-mixtral-8x7b)
* [Sao10K/Sensualize-Mixtral-bf16](https://huggingface.co/Sao10K/Sensualize-Mixtral-bf16)
* [jondurbin/bagel-dpo-8x7b-v0.2](https://huggingface.co/jondurbin/bagel-dpo-8x7b-v0.2)
* [mistralai/Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) + [Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora](https://huggingface.co/Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora)
* [smelborp/MixtralOrochi8x7B](https://huggingface.co/smelborp/MixtralOrochi8x7B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model:
  model:
    path: mistralai/Mixtral-8x7B-v0.1
dtype: bfloat16
merge_method: dare_ties
slices:
- sources:
  - layer_range: [0, 32]
    model:
      model:
        path: smelborp/MixtralOrochi8x7B
    parameters:
      density: 0.75
      weight: 0.7
  - layer_range: [0, 32]
    model:
      model:
        path: cognitivecomputations/dolphin-2.7-mixtral-8x7b
    parameters:
      density: 0.6
      weight: 0.1
  - layer_range: [0, 32]
    model:
      model:
        path: jondurbin/bagel-dpo-8x7b-v0.2
    parameters:
      density: 0.6
      weight: 0.1
  - layer_range: [0, 32]
    model:
      lora:
        path: Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora
      model:
        path: mistralai/Mixtral-8x7B-v0.1
    parameters:
      density: 0.5
      weight: 0.25
  - layer_range: [0, 32]
    model:
      model:
        path: Sao10K/Sensualize-Mixtral-bf16
    parameters:
      density: 0.5
      weight: 0.2
  - layer_range: [0, 32]
    model:
      model:
        path: mistralai/Mixtral-8x7B-v0.1
```
