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Model: YOYO-AI/Qwen2.5-7B-YOYO-super Source: Original Platform
2026-06-02 23:44:11 +08:00
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+---
+base_model:
+- mergekit-community/Qwen2.5-7B-della
+- mergekit-community/Qwen2.5-7B-ties
+- Qwen/Qwen2.5-7B-Instruct
+- Qwen/Qwen2.5-7B-Instruct-1M
+- mergekit-community/Qwen2.5-7B-ties-1M
+- Qwen/Qwen2.5-7B
+- mergekit-community/Qwen2.5-7B-della-1M
+library_name: transformers
+tags:
+- mergekit
+- merge
+license: apache-2.0
+language:
+- en
+- zh
+pipeline_tag: text-generation
+---
+# Achieve the Optimal Merged Model by Using One Basic Model and Two Fine-tuned Models!
+
+*What is the best way to merge **one base model** and **two fine-tuned models**?*
+
+## This might be the best answer at the present stage!
+
+[Qwen2.5-7B-YOYO-super](https://huggingface.co/YOYO-AI/Qwen2.5-7B-YOYO-super)
+
+[Qwen2.5-14B-YOYO-super](https://huggingface.co/YOYO-AI/Qwen2.5-14B-YOYO-super)
+
+*This is not a whim release, but the optimal result of countless merging experiments!*
+
+*Here is the formula for the **previous generation**:*
+```yaml
+models:  
+  - model: Qwen/Qwen2.5-7B-Instruct  
+    parameters:  
+      density: 1  
+      weight: 1  
+      lambda: 0.9
+  - model: Qwen/Qwen2.5-7B-Instruct-1M  
+    parameters:  
+      density: 1  
+      weight: 1  
+      lambda: 0.9  
+merge_method: della  
+base_model: Qwen/Qwen2.5-7B  
+parameters:  
+  density: 1  
+  weight: 1  
+  lambda: 0.9  
+  normalize: true  
+  int8_mask: true  
+dtype: bfloat16  
+tokenizer_source: base
+```
+*It was widely used in the merging process of the **previous generation of models***.
+
+*However, there are some **deficiencies***:
+ 
+*1.There is relatively little retention of knowledge of the basic model.*
+
+*2.The mathematical and coding abilities have declined.*
+
+## And here is the formula for this generation:
+```yaml
+models:
+  - model: Qwen/Qwen2.5-7B-instruct
+    parameters:
+      density: 1 
+      weight: 1
+      lambda: 0.9
+merge_method: della
+base_model: Qwen/Qwen2.5-7B
+parameters:
+  density: 1
+  weight: 1
+  lambda: 0.9
+  normalize: true
+  int8_mask: true
+dtype: float16
+tokenizer_source: base
+name: Qwen2.5-7B-della
+```
+```yaml
+models:
+  - model: Qwen/Qwen2.5-7B-instruct-1M
+    parameters:
+      density: 1 
+      weight: 1
+      lambda: 0.9
+merge_method: della
+base_model: Qwen/Qwen2.5-7B
+parameters:
+  density: 1
+  weight: 1
+  lambda: 0.9
+  normalize: true
+  int8_mask: true
+dtype: float16
+tokenizer_source: base
+name: Qwen2.5-7B-della-1M
+```
+```yaml
+models:
+  - model: Qwen/Qwen2.5-7B-instruct
+    parameters:
+      density: 1 
+      weight: 1
+merge_method: ties
+base_model: Qwen/Qwen2.5-7B
+parameters:
+  density: 1
+  weight: 1
+  normalize: true
+  int8_mask: true
+dtype: float16
+tokenizer_source: base
+name: Qwen2.5-7B-ties
+```
+```yaml
+models:
+  - model: Qwen/Qwen2.5-7B-instruct-1M
+    parameters:
+      density: 1 
+      weight: 1
+merge_method: ties
+base_model: Qwen/Qwen2.5-7B
+parameters:
+  density: 1
+  weight: 1
+  normalize: true
+  int8_mask: true
+dtype: float16
+tokenizer_source: base
+name: Qwen2.5-7B-ties-1M
+```
+```yaml
+merge_method: model_stock
+base_model: Qwen/Qwen2.5-7B
+models:
+  - model: mergekit-community/Qwen2.5-7B-della
+  - model: mergekit-community/Qwen2.5-7B-della-1M
+  - model: mergekit-community/Qwen2.5-7B-ties
+  - model: mergekit-community/Qwen2.5-7B-ties-1M
+  - model: Qwen/Qwen2.5-7B-instruct-1M
+  - model: Qwen/Qwen2.5-7B-instruct
+tokenizer_source: base
+int8_mask: true
+normalize: true
+dtype: float16
+```
+*Except for a slight decrease in instruction following, **significant improvements** have been achieved in all other aspects.*
+
+*This formula will also be used in the development of **the next generation of YOYO models**.*
+
+***YOYO-AI** not only releases merged models with excellent performance but also publishes a **complete and high-quality model merging formula**, hoping to promote the progress of model merging technology in the open-source community with this!*
+
+### If you can use this formula when merging models, it will be the greatest support for YOYO-AI!