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---
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
---
[](https://hf.co/QuantFactory)
# 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
```
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