---
base_model:
- berkeley-nest/Starling-LM-7B-alpha
- mlabonne/AlphaMonarch-7B
- cognitivecomputations/WestLake-7B-v2-laser
- senseable/garten2-7b
- mistralai/Mistral-7B-v0.1
library_name: transformers
tags:
- mergekit
- merge

---
# temp1

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 [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) as a base.

### Models Merged

The following models were included in the merge:
* [berkeley-nest/Starling-LM-7B-alpha](https://huggingface.co/berkeley-nest/Starling-LM-7B-alpha)
* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
* [cognitivecomputations/WestLake-7B-v2-laser](https://huggingface.co/cognitivecomputations/WestLake-7B-v2-laser)
* [senseable/garten2-7b](https://huggingface.co/senseable/garten2-7b)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: mistralai/Mistral-7B-v0.1
    # No parameters necessary for base model

  - model: cognitivecomputations/WestLake-7B-v2-laser
    parameters:
      density: 0.58
      weight:  [0.3877, 0.1636, 0.186, 0.0502]



  - model: senseable/garten2-7b
    parameters:
      density: 0.58
      weight:  [0.234, 0.2423, 0.2148, 0.2775]



  - model: berkeley-nest/Starling-LM-7B-alpha
    parameters:
      density: 0.58
      weight:  [0.1593, 0.1573, 0.1693, 0.3413]



  - model: mlabonne/AlphaMonarch-7B
    parameters:
      density: 0.58
      weight:  [0.219, 0.4368, 0.4299, 0.331]



merge_method: dare_ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  int8_mask: true
dtype: bfloat16

```