---
base_model:
- kubernetes-bad/chargen-v2
- NeverSleep/Noromaid-7B-0.4-DPO
- mlabonne/NeuralHermes-2.5-Mistral-7B
- Weyaxi/Einstein-v4-7B
- Severian/Einstein-IKM-v1-7B-LoRa
library_name: transformers
tags:
- mergekit
- merge

---
# 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 [kubernetes-bad/chargen-v2](https://huggingface.co/kubernetes-bad/chargen-v2) as a base.

### Models Merged

The following models were included in the merge:
* [NeverSleep/Noromaid-7B-0.4-DPO](https://huggingface.co/NeverSleep/Noromaid-7B-0.4-DPO)
* [mlabonne/NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)
* [Weyaxi/Einstein-v4-7B](https://huggingface.co/Weyaxi/Einstein-v4-7B) + [Severian/Einstein-IKM-v1-7B-LoRa](https://huggingface.co/Severian/Einstein-IKM-v1-7B-LoRa)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: kubernetes-bad/chargen-v2
    parameters:
      density: 1
      weight: 1
  - model: NeverSleep/Noromaid-7B-0.4-DPO
    parameters:
      density: 0.65
      weight: 0.2
  - model: Weyaxi/Einstein-v4-7B+Severian/Einstein-IKM-v1-7B-LoRa
    parameters:
      density: [0.6, 0.5, 0.4, 0.5, 0.6]
      weight: 0.15
  - model: mlabonne/NeuralHermes-2.5-Mistral-7B
    parameters:
      density: [0.4, 0.5, 0.6, 0.5, 0.4]
      weight: 0.15
merge_method: ties
base_model: kubernetes-bad/chargen-v2
parameters:
  normalize: true
dtype: bfloat16

```