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--- |
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base_model: |
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- VAGOsolutions/SauerkrautLM-v2-14b-DPO |
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- qingy2019/Qwen2.5-Math-14B-Instruct |
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- CultriX/Qwen2.5-14B-Wernickev3 |
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- CultriX/SeQwence-14Bv1 |
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- CultriX/Qwen2.5-14B-Emergedv3 |
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- CultriX/Qwen2.5-14B-Unity |
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- allknowingroger/QwenSlerp6-14B |
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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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--- |
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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 [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [CultriX/SeQwence-14Bv1](https://huggingface.co/CultriX/SeQwence-14Bv1) as a base. |
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### Models Merged |
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The following models were included in the merge: |
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* [VAGOsolutions/SauerkrautLM-v2-14b-DPO](https://huggingface.co/VAGOsolutions/SauerkrautLM-v2-14b-DPO) |
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* [qingy2019/Qwen2.5-Math-14B-Instruct](https://huggingface.co/qingy2019/Qwen2.5-Math-14B-Instruct) |
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* [CultriX/Qwen2.5-14B-Wernickev3](https://huggingface.co/CultriX/Qwen2.5-14B-Wernickev3) |
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* [CultriX/Qwen2.5-14B-Emergedv3](https://huggingface.co/CultriX/Qwen2.5-14B-Emergedv3) |
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* [CultriX/Qwen2.5-14B-Unity](https://huggingface.co/CultriX/Qwen2.5-14B-Unity) |
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* [allknowingroger/QwenSlerp6-14B](https://huggingface.co/allknowingroger/QwenSlerp6-14B) |
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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: CultriX/SeQwence-14Bv1 |
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parameters: |
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weight: 0.22 # Boosted slightly to improve general task performance |
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density: 0.62 # Prioritize generalist adaptability |
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- model: allknowingroger/QwenSlerp6-14B |
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parameters: |
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weight: 0.18 |
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density: 0.59 # Slight increase to enhance contextual reasoning (tinyHellaswag) |
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- model: CultriX/Qwen2.5-14B-Wernickev3 |
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parameters: |
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weight: 0.16 |
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density: 0.56 # Minor increase to stabilize GPQA and MUSR performance |
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- model: CultriX/Qwen2.5-14B-Emergedv3 |
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parameters: |
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weight: 0.15 # Increase weight for domain-specific expertise |
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density: 0.55 |
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- model: VAGOsolutions/SauerkrautLM-v2-14b-DPO |
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parameters: |
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weight: 0.12 |
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density: 0.56 # Enhance factual reasoning and IFEval contributions |
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- model: CultriX/Qwen2.5-14B-Unity |
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parameters: |
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weight: 0.10 |
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density: 0.53 |
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- model: qingy2019/Qwen2.5-Math-14B-Instruct |
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parameters: |
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weight: 0.10 |
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density: 0.51 # Retain focus on MATH and advanced reasoning tasks |
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merge_method: dare_ties |
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base_model: CultriX/SeQwence-14Bv1 |
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parameters: |
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normalize: true |
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int8_mask: true |
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dtype: bfloat16 |
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tokenizer_source: Qwen/Qwen2.5-14B-Instruct |
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adaptive_merge_parameters: |
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task_weights: |
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IFEval: 1.5 # Strengthened for better instruction-following |
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BBH: 1.3 |
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MATH: 1.6 # Emphasize advanced reasoning and problem-solving |
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GPQA: 1.4 # Improve factual recall and logical QA tasks |
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MUSR: 1.5 # Strengthened multi-step reasoning capabilities |
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MMLU-PRO: 1.3 # Slight boost for domain-specific multitask knowledge |
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smoothing_factor: 0.19 # Refined for smoother blending of task strengths |
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gradient_clipping: 0.88 # Tightened slightly for precise parameter contribution |
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``` |
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