Compare model weights and visualize differences
Analyze model errors with interactive pages
Request model evaluation on COCO val 2017 dataset
Upload ML model to Hugging Face Hub
Quantize a model for faster inference
Display leaderboard of language model evaluations
Pergel: A Unified Benchmark for Evaluating Turkish LLMs
Teach, test, evaluate language models with MTEB Arena
Calculate survival probability based on passenger details
Text-To-Speech (TTS) Evaluation using objective metrics.
Display model benchmark results
Search for model performance across languages and benchmarks
Convert Hugging Face models to OpenVINO format
Vis Diff is a tool designed to compare model weights and visualize differences between them. It is particularly useful for understanding how different models or versions of the same model perform and identifying discrepancies in their weights. This tool is essential for model benchmarking, allowing users to gain insights into model similarities and differences through visual representations.
What models can Vis Diff compare?
Vis Diff supports comparison of weights from various machine learning models, including but not limited to neural networks in TensorFlow, PyTorch, and Keras.
How can I interpret the visualizations?
The visualizations highlight differences in model weights, with color intensity often representing the magnitude of differences. This helps identify which parts of the model have diverged the most.
Where can I find more information or support for Vis Diff?
For additional details, documentation, or support, refer to the official Vis Diff website or its community forums.