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---
base_model:
- Qwen/Qwen2.5-14B
- Qwen/Qwen2.5-14B-Instruct
- CultriX/Qwen2.5-14B-Coder_r128
- CultriX/Qwen2.5-14B_Virtuoso-small-v2-LoRA_r128
- CultriX/Qwen2.5-14B-DeepSeek_r128
- CultriX/Qwen2.5-14B-Hyperionv3_r128
- CultriX/Qwen2.5-14B-SuperNova-Medius_r128
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 [DARE TIES](https://arxiv.org/abs/2311.03099) merge method using [Qwen/Qwen2.5-14B](https://huggingface.co/Qwen/Qwen2.5-14B) as a base.
### Models Merged
The following models were included in the merge:
* [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)
* [CultriX/Qwen2.5-14B-Coder_r128](https://huggingface.co/CultriX/Qwen2.5-14B-Coder_r128)
* [CultriX/Qwen2.5-14B_Virtuoso-small-v2-LoRA_r128](https://huggingface.co/CultriX/Qwen2.5-14B_Virtuoso-small-v2-LoRA_r128)
* [CultriX/Qwen2.5-14B-DeepSeek_r128](https://huggingface.co/CultriX/Qwen2.5-14B-DeepSeek_r128)
* [CultriX/Qwen2.5-14B-Hyperionv3_r128](https://huggingface.co/CultriX/Qwen2.5-14B-Hyperionv3_r128)
* [CultriX/Qwen2.5-14B-SuperNova-Medius_r128](https://huggingface.co/CultriX/Qwen2.5-14B-SuperNova-Medius_r128)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
# Optimized MergeKit configuration for merging extracted LoRA adapters
# into the Qwen2.5-14B-Instruct model.
base_model: Qwen/Qwen2.5-14B
models:
# Each adapter was extracted (rank=128) from its respective finetuned model.
# Their weights are set lower than the full instruct model (which is now the base)
- model: CultriX/Qwen2.5-14B-Hyperionv3_r128
parameters:
weight: 0.15 # Reduced weight relative to base
density: 1.0
lora_rank: 128 # Mark as extracted LoRA adapter
- model: CultriX/Qwen2.5-14B-Coder_r128
parameters:
weight: 0.15
density: 1.0
lora_rank: 128
- model: CultriX/Qwen2.5-14B_Virtuoso-small-v2-LoRA_r128
parameters:
weight: 0.15
density: 1.0
lora_rank: 128
- model: CultriX/Qwen2.5-14B-SuperNova-Medius_r128
parameters:
weight: 0.15
density: 1.0
lora_rank: 128
- model: CultriX/Qwen2.5-14B-DeepSeek_r128
parameters:
weight: 0.15
density: 1.0
lora_rank: 128
# (Optionally, if you wish to “re-add” a full instruct copy you could include it here
# with a higher weight—but note that Qwen2.5-14B-Instruct is already the base.)
- model: Qwen/Qwen2.5-14B-Instruct
parameters:
weight: 0.40
density: 1.0
# Merging method and overall parameters
merge_method: dare_ties # Ties corresponding weights across sources.
parameters:
weight: 1.0 # Overall scaling factor.
density: 1.0 # Overall density (typically left at 1.0).
normalize: true # Normalize each set of weights before merging.
int8_mask: true # Enable masking if using int8 quantized weights.
# Use the instruct tokenizer to ensure compatibility.
tokenizer_source: CultriX/Qwen2.5-14B_Virtuoso-small-v2-LoRA_r128
# Data type for merged weights.
dtype: bfloat16
```
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