Merge machine learning models using a YAML configuration file
Browse and submit evaluations for CaselawQA benchmarks
Calculate VRAM requirements for LLM models
View and submit language model evaluations
Quantize a model for faster inference
Evaluate AI-generated results for accuracy
Benchmark models using PyTorch and OpenVINO
Evaluate model predictions with TruLens
Calculate memory needed to train AI models
Evaluate RAG systems with visual analytics
Calculate GPU requirements for running LLMs
Download a TriplaneGaussian model checkpoint
View NSQL Scores for Models
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.