Cheng-1: Multi-Specialty Merged Language Model

Model Overview

Cheng-1 is a high-performance language model created through strategic merging of top-tier, pre-existing fine-tuned models. It excels in coding, math, translation, and roleplay without requiring additional fine-tuning. The final model was built using the model_stock method with a restore model to maintain strong instruction-following and mathematical abilities.

Development Process

1. Foundation Model - "Yell-Qwen2.5-7B-1M"

• Base Merge: Combined Qwen2.5-7B-Instruct-1M with Qwen2.5-7B using SCE merging.
• Purpose: Established a strong general-purpose foundation for later merges.

Merge Code:

merge_method: sce  
models:
  - model: Qwen/Qwen2.5-7B-Instruct-1M
  - model: Qwen/Qwen2.5-7B  
base_model: Qwen/Qwen2.5-7B-Instruct-1M  
parameters:  
  select_topk: 1  
dtype: bfloat16  
tokenizer_source: base  
normalize: true  
int8_mask: true  
name: Yell-Qwen2.5-7B-1M  

2. Domain-Specific Merges

• Coding: Merged AceCoder-Qwen2.5-7B-Ins-Rule with Yell-Qwen2.5-7B-1M.
• Translation: Merged DRT-7B with Yell-Qwen2.5-7B-1M.
• Math: Merged AceMath-7B-Instruct with Yell-Qwen2.5-7B-1M.
• Method: All three were merged using della merging, producing three intermediate models.

Merge Code:

merge_method: della  
base_model: marcuscedricridia/Yell-Qwen2.5-7B-1M 
models:  
  - model: TIGER-Lab/AceCoder-Qwen2.5-7B-Ins-Rule 
    parameters:  
      density: 1  
      weight: 1  
      lambda: 0.9  
  - model: Krystalan/DRT-7B
    parameters:  
      density: 1  
      weight: 1  
      lambda: 0.9  
  - model: nvidia/AceMath-7B-Instruct
    parameters:  
      density: 1  
      weight: 1  
      lambda: 0.9  
parameters:  
  density: 1  
  weight: 1  
  lambda: 0.9  
  normalize: true  
  int8_mask: true  
dtype: bfloat16  
tokenizer_source: base  
name: Cheng-1

3. Final Model Stock Merge

• Models Combined:
  • mergekit-della-wpunuct
  • mergekit-della-phphmhr
  • mergekit-della-qejrhsk
  • Hush-Qwen2.5-7B-RP-v1.2-1M (Roleplay model)
• Base Model: YOYO-AI/Qwen2.5-7B-it-restore
• Final Method: Used model_stock merging to integrate all models into Cheng-1.

Merge Code:

merge_method: model_stock  
base_model: YOYO-AI/Qwen2.5-7B-it-restore  
models:  
  - model: marcuscedricridia/mergekit-della-wpunuct
  - model: marcuscedricridia/mergekit-della-phphmhr
  - model: marcuscedricridia/mergekit-della-qejrhsk
  - model: marcuscedricridia/Hush-Qwen2.5-7B-RP-v1.2-1M  
dtype: bfloat16  
tokenizer_source: base  
int8_mask: true  
normalize: true  
name: Cheng-1

Benchmarks

Model: marcuscedricridia/Cheng-1
Precision: torch.bfloat16
Revision: cd8c9dd37c67c2e1b7c683fdd5e72b7f08c074b9

Average: 36.06
IFEval: 77.89
BBH: 36.54
MATH: 48.94
GPQA: 6.15
MUSR: 9.62
MMLU-PRO: 37.21

Conclusion

Cheng-1 is a versatile model optimized for multiple domains. By merging top-performing models in coding, math, translation, and roleplay, it achieves balanced and strong benchmark results without direct fine-tuning.