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README.md
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---
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base_model:
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- v000000/Qwen2.5-14B-Gutenberg-1e-Delta
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- Qwen/Qwen2.5-14B-Instruct
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library_name: transformers
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tags:
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- mergekit
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- merge
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- qwen2
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- qwen2.5
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- dpo
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license: apache-2.0
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datasets:
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- jondurbin/gutenberg-dpo-v0.1
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---
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[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
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# QuantFactory/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno-GGUF
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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
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# Original Model Card
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# Qwen2.5-14B-Gutenberg-Instruct-Slerpeno
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/64f74b6e6389380c77562762/PgoZ5eutiHDfBmuoBuDO9.png)
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--------------------------------------------------------------------------
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## GGUF from mradermacher!
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* [GGUF static](https://huggingface.co/mradermacher/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno-GGUF)
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* [GGUF Imatrix](https://huggingface.co/mradermacher/Qwen2.5-14B-Gutenberg-Instruct-Slerpeno-i1-GGUF)
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# merge
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the SLERP merge method. (*sophosympatheia gradient*)
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### Models Merged
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The following models were included in the merge:
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* [v000000/Qwen2.5-14B-Gutenberg-1e-Delta](https://huggingface.co/v000000/Qwen2.5-14B-Gutenberg-1e-Delta)
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* [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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models:
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- model: Qwen/Qwen2.5-14B-Instruct
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merge_method: slerp
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base_model: v000000/Qwen2.5-14B-Gutenberg-1e-Delta
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parameters:
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t:
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- value: [0, 0, 0.3, 0.4, 0.5, 0.6, 0.5, 0.4, 0.3, 0, 0]
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dtype: bfloat16
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```
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*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.*
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