---
base_model:
- SanjiWatsuki/Kunoichi-7B
- SanjiWatsuki/Kunoichi-DPO-v2-7B
library_name: transformers
tags:
- mergekit
- merge
license: cc-by-nc-4.0
---


<br/><br/>
8bpw/h8 exl2 quantization of [grimjim/kuno-kunoichi-v1-DPO-v2-SLERP-7B](https://huggingface.co/grimjim/kuno-kunoichi-v1-DPO-v2-SLERP-7B) using default exllamav2 calibration dataset.

---

**ORIGINAL CARD:**
# kuno-kunoichi-v1-DPO-v2-SLERP-7B

kuno-kunoichi-v1-DPO-v2-SLERP-7B is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
I'm hoping that the result is more robust against errors or when merging due to "denseness", as the two models likely implement comparable reasoning at least somewhat differently.

I've performed some testing with ChatML format prompting using temperature=1.1 and minP=0.03. The model also supports Alpaca format prompts.

[GGUF-IQ-Imatrix quants helpfully provided by Lewdiculous.](https://huggingface.co/Lewdiculous/kuno-kunoichi-v1-DPO-v2-SLERP-7B-GGUF-IQ-Imatrix)

[Q8_0 GGUF quant](https://huggingface.co/grimjim/kuno-kunoichi-v1-DPO-v2-SLERP-7B-GGUF)

## Merge Details
### Merge Method

This model was merged using the SLERP merge method.

### Models Merged

The following models were included in the merge:
* [SanjiWatsuki/Kunoichi-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-7B)
* [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
    - model: SanjiWatsuki/Kunoichi-7B
      layer_range: [0,32]
    - model: SanjiWatsuki/Kunoichi-DPO-v2-7B
      layer_range: [0,32]
merge_method: slerp
base_model: SanjiWatsuki/Kunoichi-7B
parameters:
  t:
    - value: 0.5
dtype: float16

```