Compare audio representation models using benchmark results
Explore and visualize diverse models
Browse and evaluate ML tasks in MLIP Arena
Calculate VRAM requirements for LLM models
Convert and upload model files for Stable Diffusion
Quantize a model for faster inference
Launch web-based model application
Merge machine learning models using a YAML configuration file
Evaluate model predictions with TruLens
Evaluate adversarial robustness using generative models
Display benchmark results
Display genomic embedding leaderboard
Run benchmarks on prediction models
ARCH is a tool designed for comparing audio representation models using benchmark results. It provides a comprehensive platform to evaluate and analyze different audio models against various benchmarks. ARCH is particularly useful for researchers and developers working in audio processing and machine learning fields.
• Support for multiple audio representation models: Including waveform, spectrogram, and other advanced models.
• Pre-defined benchmark datasets: Users can evaluate models on common audio tasks.
• Visualization tools: Generate plots and charts to compare model performance.
• Model zoo: Access pre-trained models for quick comparison.
• Customizable evaluation: Define specific metrics and benchmarks for tailored analysis.
pip install arch-benchmark
from arch import benchmark
results = benchmark.run(models, dataset='urbansound8k')
benchmark.visualize(results, save_path='results_plot.png')
What models are supported by ARCH?
ARCH supports a variety of pre-trained audio representation models, including popular ones like VGG Sound, PANNs, and OpenL3. Custom models can also be integrated for comparison.
Can I use my own dataset for benchmarking?
Yes, ARCH allows users to use custom datasets. Simply specify the dataset path and configuration when running the benchmark script.
How do I interpret the benchmark results?
Benchmark results are provided in a structured format, including metrics like accuracy, F1-score, and inference time. Use the visualization tools to generate plots that help compare model performance effectively.