Unnati Kendall Tau Distance

---
name: unnati-kendall-tau-distance
description: Compute unnati/kendall_tau_distance via the HuggingFace `evaluate` library. Use when the user has predictions + references and wants the canonical implementation of unnati/kendall_tau_distance.
metadata:
  skill_kind: metric
  source_lib: huggingface-evaluate
  hf_module: unnati/kendall_tau_distance
  source: library_introspection
---

# unnati-kendall-tau-distance

> Metric `unnati/kendall_tau_distance` from the HuggingFace `evaluate` library.

## When to invoke

User asks to compute `unnati/kendall_tau_distance` or wants HF evaluate's canonical version.

## Recipe

```python
import evaluate
metric = evaluate.load("unnati/kendall_tau_distance")
result = metric.compute(predictions=preds, references=refs)
print(result)
```

## Don'ts

- Don't assume your in-house `unnati/kendall_tau_distance` matches HF — version conventions vary.
- Many evaluate metrics have task-specific arguments (`average=`, `lang=`, `model_type=`); read the metric card before reporting numbers.