Compute ingyu/klue_mrc via the HuggingFace `evaluate` library. Use when the user has predictions + references and wants the canonical implementation of ingyu/klue_mrc.
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---
name: ingyu-klue-mrc
description: Compute ingyu/klue_mrc via the HuggingFace `evaluate` library. Use when the user has predictions + references and wants the canonical implementation of ingyu/klue_mrc.
metadata:
skill_kind: metric
source_lib: huggingface-evaluate
hf_module: ingyu/klue_mrc
source: library_introspection
---
# ingyu-klue-mrc
> Metric `ingyu/klue_mrc` from the HuggingFace `evaluate` library.
## When to invoke
User asks to compute `ingyu/klue_mrc` or wants HF evaluate's canonical version.
## Recipe
```python
import evaluate
metric = evaluate.load("ingyu/klue_mrc")
result = metric.compute(predictions=preds, references=refs)
print(result)
```
## Don'ts
- Don't assume your in-house `ingyu/klue_mrc` matches HF — version conventions vary.
- Many evaluate metrics have task-specific arguments (`average=`, `lang=`, `model_type=`); read the metric card before reporting numbers.