- Two tasks: one text/NLP, one audio processing/speech-to-text.- Everything in `build/` is generated or an upstream library.- Everything in `util/` is tooling for building and preparing the benchmark.# Licenses- Transformers.js: Apache 2.0, https://github.com/huggingface/transformers.js/blob/main/LICENSE- ONNX runtime: MIT, https://github.com/microsoft/onnxruntime/blob/main/LICENSE- `text-encoding` Polyfill: Unlicense OR Apache 2.0, https://github.com/inexorabletash/text-encoding/blob/master/LICENSE.md- Model `DistilBERT base uncased finetuned SST-2`: Apache 2.0, https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english- Model `openai/whisper-tiny.en`: Apache 2.0, https://huggingface.co/openai/whisper-tiny.en- Audio file for speech-to-text task: Public domain, https://www.jfklibrary.org/learn/about-jfk/historic-speeches/inaugural-address