metadata
base_model:
- SicariusSicariiStuff/Impish_QWEN_14B-1M
- deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
- Qwen/Qwen2.5-14B-Instruct-1M
- Zhihu-ai/Zhi-writing-dsr1-14b
- huihui-ai/Qwen2.5-14B-Instruct-1M-abliterated
- huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
- Qwen/Qwen2.5-14B-Instruct
- mergekit-community/Qwen2.5-14B-della-code
- tanliboy/lambda-qwen2.5-14b-dpo-test
library_name: transformers
tags:
- mergekit
- merge
license: apache-2.0
language:
- en
- zh
pipeline_tag: text-generation
From the preliminary test results, the effect is really excellent!!!
This is definitely a very promising method for model merging!
The current optimal formula ratio is: instruction: reasoning: code = 6:2:1
merge
This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method
This model was merged using the Karcher Mean merge method using Qwen/Qwen2.5-14B-Instruct as a base.
Models Merged
The following models were included in the merge:
instruction:(6)
- Qwen/Qwen2.5-14B-Instruct
- Qwen/Qwen2.5-14B-Instruct-1M
- huihui-ai/Qwen2.5-14B-Instruct-1M-abliterated
- huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
- SicariusSicariiStuff/Impish_QWEN_14B-1M
- tanliboy/lambda-qwen2.5-14b-dpo-test
reasoning:(2)
code:(1)
Configuration
The following YAML configuration was used to produce this model:
models:
- model: mergekit-community/Qwen2.5-14B-della-code
- model: Zhihu-ai/Zhi-writing-dsr1-14b
- model: deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
- model: huihui-ai/Qwen2.5-14B-Instruct-1M-abliterated
- model: huihui-ai/Qwen2.5-14B-Instruct-abliterated-v2
- model: Qwen/Qwen2.5-14B-Instruct-1M
- model: SicariusSicariiStuff/Impish_QWEN_14B-1M
- model: tanliboy/lambda-qwen2.5-14b-dpo-test
- model: Qwen/Qwen2.5-14B-Instruct
merge_method: karcher
base_model: Qwen/Qwen2.5-14B-Instruct
parameters:
max_iter: 1000
normalize: true
int8_mask: true
tokenizer_source: base
dtype: float16