Merge machine learning models using a YAML configuration file
Evaluate model predictions with TruLens
Convert Hugging Face models to OpenVINO format
Evaluate AI-generated results for accuracy
Explain GPU usage for model training
Persian Text Embedding Benchmark
Rank machines based on LLaMA 7B v2 benchmark results
Launch web-based model application
Quantize a model for faster inference
Display genomic embedding leaderboard
Measure execution times of BERT models using WebGPU and WASM
Explore and submit models using the LLM Leaderboard
Visualize model performance on function calling tasks
MergeKit-GUI is a user-friendly graphical interface designed for merging machine learning models. It simplifies the process of combining models using a YAML configuration file, making it accessible to both researchers and practitioners. The tool is particularly useful for model benchmarking and streamlines the workflow for model merging tasks.
• YAML Configuration Support: Define model merging parameters using a simple YAML file.
• GUI-Based Interface: Intuitive interface for visualizing and managing model merging processes.
• Automated Benchmarking: Easily compare performance metrics of merged models.
• Multi-Model Support: Merge models from different frameworks and formats.
• Configuration Validation: Ensure correct settings before initiating the merge.
• Real-Time Previews: Review merging results and parameters in real-time.
• Cross-Platform Compatibility: Runs on Windows, macOS, and Linux systems.
What models can I merge with MergeKit-GUI?
MergeKit-GUI supports merging models from various frameworks, including TensorFlow, PyTorch, and ONNX formats.
How do I install MergeKit-GUI?
Installation instructions are available in the official repository. Ensure you have the required dependencies installed before proceeding.
Can I customize the merging process?
Yes, the YAML configuration file allows you to define custom parameters and settings for the merging process.