README.md

---
base_model:
- microsoft/phi-3.5-mini-instruct
- AXCXEPT/Borea-Phi-3.5-mini-Instruct-Common
library_name: transformers
tags:
- mergekit
- merge
license: mit
license_link: https://huggingface.co/microsoft/Phi-3.5-mini-instruct/resolve/main/LICENSE
language:
- en
- ja
inference: true
pipeline_tag: text-generation
widget:
  - messages:
      - role: user
        content: こんにちは！
  - messages:
      - role: user
        content: 魚を捌くのは難しいですか？
  - messages:
      - role: user
        content: ナイジェリアの首都はどこですか？
  - messages:
      - role: user
        content: hello!
  - messages:
      - role: user
        content: 貝は砂浜に落ちてるものですか？
  - messages:
      - role: user
        content: おはようございます。
  - messages:
      - role: user
        content: 錫はどういうものに使われますか？
  - messages:
      - role: user
        content: 露骨とあからさまが違う言葉であることを証明してください。
  - messages:
      - role: user
        content: 你好
  - messages:
      - role: user
        content: 魚を捌くのは難しいですか？
  - messages:
      - role: user
        content: Où se trouve Shinjuku ?
  - messages:
      - role: user
        content: Bonjour!
---
This project utilizes HODACHI/Borea-Phi-3.5-mini-Instruct-Common, a model based on Phi-3.5-mini-Instruct and fine-tuned by Axcxept co., ltd.
# merge

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 [TIES](https://arxiv.org/abs/2306.01708) merge method using [microsoft/phi-3.5-mini-instruct](https://huggingface.co/microsoft/phi-3.5-mini-instruct) as a base.

### Models Merged

The following models were included in the merge:
* [AXCXEPT/Borea-Phi-3.5-mini-Instruct-Common](https://huggingface.co/AXCXEPT/Borea-Phi-3.5-mini-Instruct-Common)

### Configuration

The following YAML configuration was used to produce this model:

```yaml

models:
  - model: AXCXEPT/Borea-Phi-3.5-mini-Instruct-Common
    parameters:
      weight: 1
      density: 1
merge_method: ties
base_model: microsoft/phi-3.5-mini-instruct
parameters:
  weight: 1
  density: 1
  normalize: true
  int8_mask: true
dtype: float16
```