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Runnable evaluation template scripts for ML tasks. Match task_type to template, adapt CONFIG, run.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Use this skill for Hugging Face Dataset Viewer API workflows that fetch subset/split metadata, paginate rows, search text, apply filters, download parquet URLs, and read size or statistics.
Create and manage datasets on Hugging Face Hub. Supports initializing repos, defining configs/system prompts, streaming row updates, and SQL-based dataset querying/transformation. Designed to work alongside HF MCP server for comprehensive dataset workflows.
Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.
| name | eval-templates |
| description | Runnable evaluation template scripts for ML tasks. Match task_type to template, adapt CONFIG, run. |
Match the plan's task_type to a template in scripts/, adapt CONFIG variables, run via run_code_in_docker.
| task_type | Script | Notes |
|---|---|---|
| extractive_qa | eval_qa.py | Pipeline + no-answer threshold for SQuAD v2 |
| nli, classification | eval_nli.py | Label remapping, filter label=-1 |
| zero_shot | eval_zero_shot.py | Pipeline + candidate_labels |
| multilabel | eval_multilabel.py | Single-label argmax for accuracy metric |
| summarization | eval_summarization.py | Seq2Seq + ROUGE |
| ner | eval_ner.py | Token classification + seqeval, parquet fallback |
| vision | eval_vision.py | AutoImageProcessor, grayscale→RGB |
| sentiment | eval_sentiment.py | Standard classification |
| multiple_choice | eval_multiple_choice.py | vLLM + conditional log-likelihood |
cat scripts/eval_<type>.py