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---
base_model:
- arcee-ai/Virtuoso-Small
- CultriX/Qwen2.5-14B-Wernicke
- CultriX/SeQwence-14B-EvolMerge
- Qwen/Qwen2.5-14B-Instruct
- v000000/Qwen2.5-Lumen-14B
- 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 [task arithmetic](https://arxiv.org/abs/2212.04089) merge method using [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) as a base.

### Models Merged

The following models were included in the merge:
* [arcee-ai/Virtuoso-Small](https://huggingface.co/arcee-ai/Virtuoso-Small)
* [CultriX/Qwen2.5-14B-Wernicke](https://huggingface.co/CultriX/Qwen2.5-14B-Wernicke)
* [CultriX/SeQwence-14B-EvolMerge](https://huggingface.co/CultriX/SeQwence-14B-EvolMerge)
* [v000000/Qwen2.5-Lumen-14B](https://huggingface.co/v000000/Qwen2.5-Lumen-14B)
* [CultriX/SeQwence-14Bv1](https://huggingface.co/CultriX/SeQwence-14Bv1)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: CultriX/Qwen2.5-14B-Wernicke
    parameters:
      weight: 0.318      # Strong performance in GPQA, MMLU-PRO
      density: 0.6        # Retain 60% of significant parameters
  - model: arcee-ai/Virtuoso-Small
    parameters:
      weight: 0.273      # Exceptional IFEval and MATH Level 5 capabilities
      density: 0.6        # Retain 60% of significant parameters
  - model: CultriX/SeQwence-14B-EvolMerge
    parameters:
      weight: 0.182      # MUSR and balanced contributions to Truthful QA and MMLU
      density: 0.5        # Retain 50% of significant parameters
  - model: CultriX/SeQwence-14Bv1
    parameters:
      weight: 0.136      # Provides diverse data and generalization
      density: 0.4        # Retain 40% of significant parameters
  - model: v000000/Qwen2.5-Lumen-14B
    parameters:
      weight: 0.091      # Enhances creative and narrative tasks
      density: 0.5        # Retain 50% for task diversity
base_model: Qwen/Qwen2.5-14B-Instruct
merge_method: task_arithmetic
parameters:
  normalize: true       # Ensures parameter scaling compatibility
  int8_mask: true       # Optimizes memory and computational efficiency
dtype: bfloat16
tokenizer_source: Qwen/Qwen2.5-14B-Instruct

```