---
base_model:
- huihui-ai/Llama-3.1-Tulu-3-70B-abliterated
- migtissera/Tess-3-Llama-3.1-70B
- Nexesenex/Llama_3.x_70b_L3.3_Dolphin_128K_v1.02
- huihui-ai/Tess-R1-Limerick-Llama-3.1-70B-abliterated
- mlabonne/Hermes-3-Llama-3.1-70B-lorablated
- nbeerbower/Llama-3.1-Nemotron-lorablated-70B
library_name: transformers
tags:
- mergekit
- merge
---
# about

Original name : Llama_3.x_70b_Dolnemhertulimtess_v1.0

Also known as : Llama_3.x_70b_Dolmen_v1.0 (1.1 will come soon)

This model is essentially a Llama 3.1 smart brick based on by a 3.0->3.3 "port", to be used in second level merges.

This time, for the base, I used a Llama 3.0 Dolphin 2.9.1/Llama 3.3 instruct abliterated merge, in order to get both the capabilities of each model, and notably Dolphin, not ported on Llama 70b 3.1 or 3.3 by CognitiveComputations.

Then, I added the best 'instructions oriented' finetunes I know, simple as that.

The model is highly uncensored, quite intelligent, and can be used as a standalone.

---
# 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 [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [Nexesenex/Llama_3.x_70b_L3.3_Dolphin_128K_v1.02](https://huggingface.co/Nexesenex/Llama_3.x_70b_L3.3_Dolphin_128K_v1.02) as a base.

### Models Merged

The following models were included in the merge:
* [huihui-ai/Llama-3.1-Tulu-3-70B-abliterated](https://huggingface.co/huihui-ai/Llama-3.1-Tulu-3-70B-abliterated)
* [migtissera/Tess-3-Llama-3.1-70B](https://huggingface.co/migtissera/Tess-3-Llama-3.1-70B)
* [huihui-ai/Tess-R1-Limerick-Llama-3.1-70B-abliterated](https://huggingface.co/huihui-ai/Tess-R1-Limerick-Llama-3.1-70B-abliterated)
* [mlabonne/Hermes-3-Llama-3.1-70B-lorablated](https://huggingface.co/mlabonne/Hermes-3-Llama-3.1-70B-lorablated)
* [nbeerbower/Llama-3.1-Nemotron-lorablated-70B](https://huggingface.co/nbeerbower/Llama-3.1-Nemotron-lorablated-70B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
merge_method: model_stock
models:
  - model: Nexesenex/Llama_3.x_70b_L3.3_Dolphin_128K_v1.02
    parameters:
      weight: 1.0
  - model: nbeerbower/Llama-3.1-Nemotron-lorablated-70B
    parameters:
      weight: 1.0
  - model: mlabonne/Hermes-3-Llama-3.1-70B-lorablated
    parameters:
      weight: 1.0
  - model: huihui-ai/Llama-3.1-Tulu-3-70B-abliterated
    parameters:
      weight: 1.0
  - model: huihui-ai/Tess-R1-Limerick-Llama-3.1-70B-abliterated
    parameters:
      weight: 1.0
  - model: migtissera/Tess-3-Llama-3.1-70B
    parameters:
      weight: 1.0
base_model: Nexesenex/Llama_3.x_70b_L3.3_Dolphin_128K_v1.02
dtype: bfloat16
out_dtype: bfloat16
parameters:
  int8_mask: true
  normalize: true
  rescale: false
  filter_wise: false
  smooth: false
  allow_negative_weights: false
chat_template: auto
tokenizer:
  source: union
```