README.md

---

base_model:
- unsloth/gemma-2-9b-it
- princeton-nlp/gemma-2-9b-it-SimPO
- wzhouad/gemma-2-9b-it-WPO-HB
- nbeerbower/Gemma2-Gutenberg-Doppel-9B
library_name: transformers
tags:
- mergekit
- merge


---

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# QuantFactory/Gemma-2-Ataraxy-Doppel-9B-GGUF
This is quantized version of [lemon07r/Gemma-2-Ataraxy-Doppel-9B](https://huggingface.co/lemon07r/Gemma-2-Ataraxy-Doppel-9B) created using llama.cpp

# Original Model Card

# Gemma-2-Ataraxy-Doppel-9B

One last test model.. that you should ignore again.

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 della merge method using [unsloth/gemma-2-9b-it](https://huggingface.co/unsloth/gemma-2-9b-it) as a base.

### Models Merged

The following models were included in the merge:
* [princeton-nlp/gemma-2-9b-it-SimPO](https://huggingface.co/princeton-nlp/gemma-2-9b-it-SimPO)
* [wzhouad/gemma-2-9b-it-WPO-HB](https://huggingface.co/wzhouad/gemma-2-9b-it-WPO-HB)
* [nbeerbower/Gemma2-Gutenberg-Doppel-9B](https://huggingface.co/nbeerbower/Gemma2-Gutenberg-Doppel-9B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
base_model: unsloth/gemma-2-9b-it
dtype: bfloat16
merge_method: della
parameters:
  epsilon: 0.1
  int8_mask: 1.0
  lambda: 1.0
  normalize: 1.0
slices:
- sources:
  - layer_range: [0, 42]
    model: unsloth/gemma-2-9b-it
  - layer_range: [0, 42]
    model: wzhouad/gemma-2-9b-it-WPO-HB
    parameters:
      density: 0.55
      weight: 0.6
  - layer_range: [0, 42]
    model: princeton-nlp/gemma-2-9b-it-SimPO
    parameters:
      density: 0.35
      weight: 0.6
  - layer_range: [0, 42]
    model: nbeerbower/Gemma2-Gutenberg-Doppel-9B
    parameters:
      density: 0.25
      weight: 0.4
```