231  huggingface-evaluate(1) - Kailash Tool Reference

231.1 huggingface-evaluate

huggingface-evaluate - HuggingFace Evaluate — library for easily evaluating ML models and datasets (the hub evaluate package).

Layer DEFENCE
Category d-03-assurance-evals-benchmarks
Safety class safe
Licence Apache-2.0
Upstream github.com/huggingface/evaluate

231.1.1 NAME

huggingface-evaluate - HuggingFace Evaluate — library for easily evaluating ML models and datasets (the hub evaluate package).

231.1.2 SYNOPSIS & usage

Derived from the upstream README at generation time; verify against --help where the tool is installed.

pip install evaluate
pip install evaluate[template]

231.1.3 DESCRIPTION (upstream)

Tip: For more recent evaluation approaches, for example for evaluating LLMs, we recommend our newer and more actively maintained library LightEval. 🤗 Evaluate is a library that makes evaluating and comparing models and reporting their performance easier and more standardized. It currently contains: - implementations of dozens of popular metrics: the existing metrics cover a variety of tasks spanning from NLP to Computer Vision, and include dataset-specific metrics for datasets. With a simple command like accuracy = load("accuracy"), get any of these metrics ready to use for evaluating a ML model in any framework (Numpy/Pandas/PyTorch/Te

231.1.4 CONFIGURATION (detected)

Config-surface markers detected in the upstream README (2 matches, e.g. ci.yml, ci.yml). A full config reference page for this tool is queued under the config-page policy — this line is the detection record, not the page.

231.1.5 SEE ALSO

ref: pin - verified 2026-10-14