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Model: CultriX/Qwen2.5-14B-Brocav3
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---
base_model:
- qingy2019/Qwen2.5-Math-14B-Instruct
- djuna/Q2.5-Veltha-14B-0.5
- CultriX/Qwen2.5-14B-Wernickev3
- CultriX/Qwenfinity-2.5-14B
- allknowingroger/QwenSlerp6-14B
- CultriX/Qwen2.5-14B-Broca
- sometimesanotion/Qwen2.5-14B-Vimarckoso
- CultriX/SeQwence-14Bv1
library_name: transformers
tags:
- mergekit
- merge
---
# 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 della_linear merge method using [CultriX/Qwen2.5-14B-Wernickev3](https://huggingface.co/CultriX/Qwen2.5-14B-Wernickev3) as a base.
### Models Merged
The following models were included in the merge:
* [qingy2019/Qwen2.5-Math-14B-Instruct](https://huggingface.co/qingy2019/Qwen2.5-Math-14B-Instruct)
* [djuna/Q2.5-Veltha-14B-0.5](https://huggingface.co/djuna/Q2.5-Veltha-14B-0.5)
* [CultriX/Qwenfinity-2.5-14B](https://huggingface.co/CultriX/Qwenfinity-2.5-14B)
* [allknowingroger/QwenSlerp6-14B](https://huggingface.co/allknowingroger/QwenSlerp6-14B)
* [CultriX/Qwen2.5-14B-Broca](https://huggingface.co/CultriX/Qwen2.5-14B-Broca)
* [sometimesanotion/Qwen2.5-14B-Vimarckoso](https://huggingface.co/sometimesanotion/Qwen2.5-14B-Vimarckoso)
* [CultriX/SeQwence-14Bv1](https://huggingface.co/CultriX/SeQwence-14Bv1)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
merge_method: della_linear
base_model: CultriX/Qwen2.5-14B-Wernickev3
dtype: bfloat16
parameters:
epsilon: 0.012 # Further reduced to ensure ultra-fine parameter scaling for precision.
lambda: 1.4 # Stronger emphasis on significant model contributions.
normalize: true # Balances the parameter integration for stability.
adaptive_merge_parameters:
task_weights:
tinyArc: 1.6 # Prioritizes logical reasoning improvements.
tinyHellaswag: 1.5 # Strengthened contextual understanding and consistency.
tinyMMLU: 1.65 # Enhanced domain knowledge for multitask benchmarks.
tinyTruthfulQA: 1.9 # Maximized for accurate factual reasoning and QA.
tinyTruthfulQA_mc1: 1.7 # Balanced focus for multiple-choice reasoning.
tinyWinogrande: 1.75 # Advanced reasoning and contextual prediction improvement.
IFEval: 1.9 # Instruction-following tasks boosted by multitask contributors.
BBH: 1.7 # Complex reasoning is supported by logical base models.
MATH: 2.1 # Highest priority, focusing on mathematical excellence.
GPQA: 1.8 # Boosted graduate-level QA capabilities.
MUSR: 1.9 # Nuanced multi-step reasoning strengthened further.
MMLU-PRO: 1.8 # Domain multitask performance maximized.
smoothing_factor: 0.1 # Precisely tuned for smooth task-specific blending.
gradient_clipping:
CultriX/Qwen2.5-14B-Wernickev3: 0.86 # Backbone stability with slightly reduced clipping.
CultriX/Qwenfinity-2.5-14B: 0.83 # Consistent multitask integration.
djuna/Q2.5-Veltha-14B-0.5: 0.91 # Strengthened advanced reasoning contributions.
CultriX/Qwen2.5-14B-Broca: 0.85 # Logical reasoning enhancements stabilized.
qingy2019/Qwen2.5-Math-14B-Instruct: 0.93 # Mathematically focused tasks maximized.
CultriX/SeQwence-14Bv1: 0.88 # Generalist multitask support.
sometimesanotion/Qwen2.5-14B-Vimarckoso: 0.89 # Balanced multi-step reasoning contributions.
allknowingroger/QwenSlerp6-14B: 0.87 # Contextual and logical reasoning integration refined.
models:
- model: CultriX/Qwen2.5-14B-Wernickev3
parameters:
weight: 0.26 # Core backbone for multitask reasoning.
density: 0.7 # Slight increase to preserve critical reasoning parameters.
- model: CultriX/Qwenfinity-2.5-14B
parameters:
weight: 0.23 # Comprehensive multitask performer.
density: 0.65
- model: djuna/Q2.5-Veltha-14B-0.5
parameters:
weight: 0.22 # Advanced reasoning support for GPQA and MUSR.
density: 0.72
- model: CultriX/Qwen2.5-14B-Broca
parameters:
weight: 0.15 # Logical reasoning and factual QA enhancements.
density: 0.65
- model: qingy2019/Qwen2.5-Math-14B-Instruct
parameters:
weight: 0.18 # Mathematical reasoning priority.
density: 0.73
- model: CultriX/SeQwence-14Bv1
parameters:
weight: 0.14 # Generalist multitask backbone.
density: 0.63
- model: sometimesanotion/Qwen2.5-14B-Vimarckoso
parameters:
weight: 0.12 # Multi-step reasoning tasks contributor.
density: 0.6
- model: allknowingroger/QwenSlerp6-14B
parameters:
weight: 0.1 # Contextual reasoning improvements.
density: 0.62
tokenizer_source: CultriX/Qwen2.5-14B-Wernickev3
```

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{
"_name_or_path": "CultriX/Qwen2.5-14B-Wernickev3",
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merge_method: della_linear
base_model: CultriX/Qwen2.5-14B-Wernickev3
dtype: bfloat16
parameters:
epsilon: 0.012 # Further reduced to ensure ultra-fine parameter scaling for precision.
lambda: 1.4 # Stronger emphasis on significant model contributions.
normalize: true # Balances the parameter integration for stability.
adaptive_merge_parameters:
task_weights:
tinyArc: 1.6 # Prioritizes logical reasoning improvements.
tinyHellaswag: 1.5 # Strengthened contextual understanding and consistency.
tinyMMLU: 1.65 # Enhanced domain knowledge for multitask benchmarks.
tinyTruthfulQA: 1.9 # Maximized for accurate factual reasoning and QA.
tinyTruthfulQA_mc1: 1.7 # Balanced focus for multiple-choice reasoning.
tinyWinogrande: 1.75 # Advanced reasoning and contextual prediction improvement.
IFEval: 1.9 # Instruction-following tasks boosted by multitask contributors.
BBH: 1.7 # Complex reasoning is supported by logical base models.
MATH: 2.1 # Highest priority, focusing on mathematical excellence.
GPQA: 1.8 # Boosted graduate-level QA capabilities.
MUSR: 1.9 # Nuanced multi-step reasoning strengthened further.
MMLU-PRO: 1.8 # Domain multitask performance maximized.
smoothing_factor: 0.1 # Precisely tuned for smooth task-specific blending.
gradient_clipping:
CultriX/Qwen2.5-14B-Wernickev3: 0.86 # Backbone stability with slightly reduced clipping.
CultriX/Qwenfinity-2.5-14B: 0.83 # Consistent multitask integration.
djuna/Q2.5-Veltha-14B-0.5: 0.91 # Strengthened advanced reasoning contributions.
CultriX/Qwen2.5-14B-Broca: 0.85 # Logical reasoning enhancements stabilized.
qingy2019/Qwen2.5-Math-14B-Instruct: 0.93 # Mathematically focused tasks maximized.
CultriX/SeQwence-14Bv1: 0.88 # Generalist multitask support.
sometimesanotion/Qwen2.5-14B-Vimarckoso: 0.89 # Balanced multi-step reasoning contributions.
allknowingroger/QwenSlerp6-14B: 0.87 # Contextual and logical reasoning integration refined.
models:
- model: CultriX/Qwen2.5-14B-Wernickev3
parameters:
weight: 0.26 # Core backbone for multitask reasoning.
density: 0.7 # Slight increase to preserve critical reasoning parameters.
- model: CultriX/Qwenfinity-2.5-14B
parameters:
weight: 0.23 # Comprehensive multitask performer.
density: 0.65
- model: djuna/Q2.5-Veltha-14B-0.5
parameters:
weight: 0.22 # Advanced reasoning support for GPQA and MUSR.
density: 0.72
- model: CultriX/Qwen2.5-14B-Broca
parameters:
weight: 0.15 # Logical reasoning and factual QA enhancements.
density: 0.65
- model: qingy2019/Qwen2.5-Math-14B-Instruct
parameters:
weight: 0.18 # Mathematical reasoning priority.
density: 0.73
- model: CultriX/SeQwence-14Bv1
parameters:
weight: 0.14 # Generalist multitask backbone.
density: 0.63
- model: sometimesanotion/Qwen2.5-14B-Vimarckoso
parameters:
weight: 0.12 # Multi-step reasoning tasks contributor.
density: 0.6
- model: allknowingroger/QwenSlerp6-14B
parameters:
weight: 0.1 # Contextual reasoning improvements.
density: 0.62
tokenizer_source: CultriX/Qwen2.5-14B-Wernickev3

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