Gorkaartola Metric For Tp Fp Samples

---
name: gorkaartola-metric-for-tp-fp-samples
description: Compute gorkaartola/metric_for_tp_fp_samples via the HuggingFace `evaluate` library. Use when the user has predictions + references and wants the canonical implementation of gorkaartola/metric_for_tp_fp_samples.
metadata:
  skill_kind: metric
  source_lib: huggingface-evaluate
  hf_module: gorkaartola/metric_for_tp_fp_samples
  source: library_introspection
---

# gorkaartola-metric-for-tp-fp-samples

> Metric `gorkaartola/metric_for_tp_fp_samples` from the HuggingFace `evaluate` library.

## When to invoke

User asks to compute `gorkaartola/metric_for_tp_fp_samples` or wants HF evaluate's canonical version.

## Recipe

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

## Don'ts

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