Merge machine learning models using a YAML configuration file
Browse and filter machine learning models by category and modality
Optimize and train foundation models using IBM's FMS
Multilingual Text Embedding Model Pruner
Rank machines based on LLaMA 7B v2 benchmark results
Compare LLM performance across benchmarks
Open Persian LLM Leaderboard
Convert Hugging Face models to OpenVINO format
Browse and submit LLM evaluations
Calculate memory needed to train AI models
Convert Hugging Face model repo to Safetensors
Display and submit LLM benchmarks
Push a ML model to Hugging Face Hub
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.