Glazkov Mars

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

qhjqhj00 b4ec627 774 B Updated 3 repo stars

File contents

glazkov-mars

Metric Glazkov/mars from the HuggingFace evaluate library.

When to invoke

User asks to compute Glazkov/mars or wants HF evaluate's canonical version.

Recipe

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

Don'ts

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

qhjqhj00/research-skills-pool/tree/main/skill-factory/output/glazkov-mars commit b4ec6272e3

Frequently asked questions

npx skillmds add qhjqhj00/glazkov-mars