Merge multiple fine-tuned models using mergekit to combine capabilities without retraining. Use when creating specialized models by blending domain-specific expertise (math + coding + chat), improving performance beyond single models, or experimenting rapidly with model variants. Covers SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.
Use Model Merging when you need to:
Success Stories: Marcoro14-7B-slerp (best on Open LLM Leaderboard 02/2024), many top HuggingFace models use merging
Tools: mergekit (Arcee AI), LazyMergekit, Model Soup
# Install mergekit
git clone https://github.com/arcee-ai/mergekit.git
cd mergekit
pip install -e .
# Or via pip
pip install mergekit
# Optional: Transformer library
pip install transformers torch
# config.yml - Merge two models with equal weights
merge_method: linear