README.md

---

base_model:
- v000000/Qwen2.5-14B-Gutenberg-1e-Delta
- Qwen/Qwen2.5-14B-Instruct
library_name: transformers
tags:
- mergekit
- merge
- qwen2
- qwen2.5
- dpo
license: apache-2.0
datasets:
- jondurbin/gutenberg-dpo-v0.1

---

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# QuantFactory/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno-GGUF
This is quantized version of [v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno](https://huggingface.co/v000000/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno) created using llama.cpp

# Original Model Card


# Qwen2.5-14B-Gutenberg-Instruct-Slerpeno

![image/png](https://cdn-uploads.huggingface.co/production/uploads/64f74b6e6389380c77562762/PgoZ5eutiHDfBmuoBuDO9.png)

--------------------------------------------------------------------------

## GGUF from mradermacher!

* [GGUF static](https://huggingface.co/mradermacher/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno-GGUF)

* [GGUF Imatrix](https://huggingface.co/mradermacher/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno-i1-GGUF)

# 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 SLERP merge method. (*sophosympatheia gradient*)

### Models Merged

The following models were included in the merge:
* [v000000/Qwen2.5-14B-Gutenberg-1e-Delta](https://huggingface.co/v000000/Qwen2.5-14B-Gutenberg-1e-Delta)
* [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: Qwen/Qwen2.5-14B-Instruct
merge_method: slerp
base_model: v000000/Qwen2.5-14B-Gutenberg-1e-Delta
parameters:
  t:
    - value: [0, 0, 0.3, 0.4, 0.5, 0.6, 0.5, 0.4, 0.3, 0, 0]
dtype: bfloat16
```

*The idea here is that Gutenberg DPO stays in the output/input 100% while merging smoothly with the base instruct model in the deeper layers to heal loss and increase intelligence.*