---
base_model:
- Steelskull/Q2.5-MS-Mistoria-72b-v2
- EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2
- Sao10K/72B-Qwen2.5-Kunou-v1
- zetasepic/Qwen2.5-72B-Instruct-abliterated
- spow12/ChatWaifu_72B_v2.2
library_name: transformers
tags:
- mergekit
- merge
license: other
license_name: qwen
---
After some success with my merging my favorite Llama 3 models, I decided to try my hand on some Qwen 2.5 models I have tried and enjoyed. I never quite got fully onto the Qwen bandwagon as I always preferred LLaMa, but a lot of folks swear by Qwen. In my limited experience with Qwen I have enjoyed these models and merged something decent I think. For this merge I went for an default parameter Della method.
# 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 della_linear merge method using [zetasepic/Qwen2.5-72B-Instruct-abliterated](https://huggingface.co/zetasepic/Qwen2.5-72B-Instruct-abliterated) as a base.

### Models Merged

The following models were included in the merge:
* [Steelskull/Q2.5-MS-Mistoria-72b-v2](https://huggingface.co/Steelskull/Q2.5-MS-Mistoria-72b-v2)
* [EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2)
* [Sao10K/72B-Qwen2.5-Kunou-v1](https://huggingface.co/Sao10K/72B-Qwen2.5-Kunou-v1)
* [spow12/ChatWaifu_72B_v2.2](https://huggingface.co/spow12/ChatWaifu_72B_v2.2)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: spow12/ChatWaifu_72B_v2.2
    parameters:
      weight: 0.25
  - model: EVA-UNIT-01/EVA-Qwen2.5-72B-v0.2
    parameters:
      weight: 0.25
  - model: Steelskull/Q2.5-MS-Mistoria-72b-v2
    parameters:
      weight: 0.25
  - model: Sao10K/72B-Qwen2.5-Kunou-v1
    parameters:
      weight: 0.25
merge_method: della_linear
base_model: zetasepic/Qwen2.5-72B-Instruct-abliterated
dtype: bfloat16
tokenizer_source: union
```