Weights Merging (mergekit)
Toolkit for merging multiple LLMs into a single model.
About
mergekit by Arcee AI is a toolkit for merging the weights of multiple pretrained language models into a single model without further training. It implements merge methods including linear, SLERP, TIES, DARE, and passthrough, and uses an out-of-core approach so elaborate merges run on CPU or with as little as 8 GB of VRAM. It is widely used to create custom model blends. Released under the LGPL-3.0 license.
Reviews (0)
Leave a Review
No reviews yet. Be the first to review!
Details
- Category
- Model Training & Fine-Tuning
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Easy (2/5)
- License
- Apache-2.0
- Added
- Apr 3, 2026
Related Tools
Training scripts for Stable Diffusion fine-tuning with LoRA and DreamBooth.
No-code tool by Hugging Face for training ML models automatically.
All-in-one Stable Diffusion fine-tuning tool with intuitive GUI.
Parameter-efficient fine-tuning technique that adapts large models with minimal trainable parameters.
Library for post-training foundation models with SFT, DPO, GRPO, and other RL methods.
Efficient LLM quantization preserving important weight channels.