Merge machine learning models using a YAML configuration file
Track, rank and evaluate open LLMs and chatbots
Calculate memory needed to train AI models
Evaluate open LLMs in the languages of LATAM and Spain.
Display leaderboard of language model evaluations
Teach, test, evaluate language models with MTEB Arena
Compare code model performance on benchmarks
Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
Explain GPU usage for model training
Convert and upload model files for Stable Diffusion
Display benchmark results
Evaluate LLM over-refusal rates with OR-Bench
Load AI models and prepare your space
Mergekit-gui is a graphical user interface designed for merging machine learning models. It simplifies the process of combining models using a YAML configuration file, making it easier to manage and deploy merged models. This tool is particularly useful for model benchmarking and streamlines workflows in machine learning development.
• Model Merging: Merge multiple machine learning models into a single model using a YAML configuration file.
• Benchmarking Support: Includes features to benchmark the performance of merged models against individual models.
• Version Control: Tracks different versions of merged models for easy comparison and deployment.
• User-Friendly Interface: Provides a graphical interface for visualizing and managing the merging process.
What is the purpose of the YAML configuration file?
The YAML configuration file defines which models to merge, their respective weights, and other parameters to ensure the merging process meets your requirements.
Can I use mergekit-gui for non-machine learning tasks?
No, mergekit-gui is specifically designed for merging machine learning models and is not intended for general-purpose file merging.
Is mergekit-gui compatible with all machine learning frameworks?
Mergekit-gui supports popular frameworks like TensorFlow and PyTorch. Check the official documentation for a full list of supported frameworks.