---
base_model:
- meta-llama/Meta-Llama-3-8B-Instruct
- VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct
- DeepMount00/Llama-3-8b-Ita
- failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
- jpacifico/French-Alpaca-Llama3-8B-Instruct-v1.0
- nbeerbower/llama-3-gutenberg-8B
library_name: transformers
tags:
- mergekit
- merge
license: apache-2.0
---
# ties

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 [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) as a base.

### Models Merged

The following models were included in the merge:
* [VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct](https://huggingface.co/VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct)
* [DeepMount00/Llama-3-8b-Ita](https://huggingface.co/DeepMount00/Llama-3-8b-Ita)
* [failspy/Meta-Llama-3-8B-Instruct-abliterated-v3](https://huggingface.co/failspy/Meta-Llama-3-8B-Instruct-abliterated-v3)
* [jpacifico/French-Alpaca-Llama3-8B-Instruct-v1.0](https://huggingface.co/jpacifico/French-Alpaca-Llama3-8B-Instruct-v1.0)
* [nbeerbower/llama-3-gutenberg-8B](https://huggingface.co/nbeerbower/llama-3-gutenberg-8B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: meta-llama/Meta-Llama-3-8B-Instruct
    parameters:
      density: 0.5
      weight: 1.0
  - model: failspy/Meta-Llama-3-8B-Instruct-abliterated-v3
    parameters:
      density: 0.5
      weight: 1.0
  - model: VAGOsolutions/Llama-3-SauerkrautLM-8b-Instruct
    parameters:
      density: 0.5
      weight: 1.0
  - model: DeepMount00/Llama-3-8b-Ita
    parameters:
      density: 0.5
      weight: 1.0
  - model: nbeerbower/llama-3-gutenberg-8B
    parameters:
      density: 0.5
      weight: 1.0
  - model: jpacifico/French-Alpaca-Llama3-8B-Instruct-v1.0
    parameters:
      density: 0.5
      weight: 1.0
merge_method: ties
tokenizer_source: union
base_model: meta-llama/Meta-Llama-3-8B-Instruct
parameters:
  int8_mask: true
dtype: bfloat16
```