README.md

---
base_model:
- Qwen/Qwen2.5-7B
- Qwen/Qwen2.5-Coder-7B
- Qwen/Qwen2.5-7B-Instruct
- Qwen/Qwen2.5-Math-7B
library_name: transformers
tags:
- mergekit
- merge

---
# nthehai01/Qwen2.5-7B-Instruct-Math-Code-breadcrumbs

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

## Performance
|             Metric              |Value|
|---------------------------------|----:|
|GSM8k (zero-shot)                |90.06|
|HellaSwag (zero-Shot)            |82.77|
|MBPP (zero-shot)                 |62.21|

## Merge Details
### Merge Method

This model was merged using the [Model Breadcrumbs](https://arxiv.org/abs/2312.06795) merge method using [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) as a base.

### Models Merged

The following models were included in the merge:
* [Qwen/Qwen2.5-Coder-7B](https://huggingface.co/Qwen/Qwen2.5-Coder-7B)
* [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)
* [Qwen/Qwen2.5-Math-7B](https://huggingface.co/Qwen/Qwen2.5-Math-7B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: Qwen/Qwen2.5-7B
dtype: bfloat16
merge_method: breadcrumbs
parameters:
  lambda: 0.9075603207928135
  normalize: 1.0
slices:
- sources:
  - layer_range: [0, 28]
    model: Qwen/Qwen2.5-7B
  - layer_range: [0, 28]
    model: Qwen/Qwen2.5-Math-7B
    parameters:
      density: 0.11722197443445775
      gamma: 0.07547691839721048
      weight: 0.17267293536872041
  - layer_range: [0, 28]
    model: Qwen/Qwen2.5-Coder-7B
    parameters:
      density: 0.48352747334554935
      gamma: 0.0753405327865558
      weight: 0.11164770709858211
  - layer_range: [0, 28]
    model: Qwen/Qwen2.5-7B-Instruct
    parameters:
      density: 0.8190520808683315
      gamma: 0.022307694128235696
      weight: 0.7626295102691242
```