Langdonholmes Cohen Weighted Kappa

Compute langdonholmes/cohen_weighted_kappa via the HuggingFace `evaluate` library. Use when the user has predictions + references and wants the canonical implementation of langdonholmes/cohen_weighted_kappa.

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langdonholmes-cohen-weighted-kappa

Metric langdonholmes/cohen_weighted_kappa from the HuggingFace evaluate library.

When to invoke

User asks to compute langdonholmes/cohen_weighted_kappa or wants HF evaluate's canonical version.

Recipe

import evaluate
metric = evaluate.load("langdonholmes/cohen_weighted_kappa")
result = metric.compute(predictions=preds, references=refs)
print(result)

Don'ts

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

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Frequently asked questions

npx skillmds add qhjqhj00/langdonholmes-cohen-weighted-kappa