Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
< 1K
ArXiv:
Tags:
evaluation
License:
Commit
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Parent(s):
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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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---
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To create the dataset, we do the following for our internal tooling.
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* rename `turns` to `prompts`,
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* add empty `reference` to remaining prompts (for HF Datasets),
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* Use the following code to load and save as a dataset
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```python
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from datasets import load_dataset
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import hashlib
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data = load_dataset("json", data_files="https://huggingface.co/datasets/HuggingFaceH4/mt_bench_prompts/raw/main/raw/question.jsonl", split="train")
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# %% create_dataset.ipynb 11
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def format_example(example):
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return {
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"prompt": example["prompt"],
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"prompt_id": int(hashlib.sha256(''.join(example["prompt"]).encode("utf-8")).hexdigest(), 16) % (10 ** 8),
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"category": example["category"],
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"reference": example["reference"],
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}
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formatted_ds = data.map(format_example, num_proc=6, remove_columns=data.column_names)
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#
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formatted_ds.push_to_hub("HuggingFaceH4/mt_bench_prompts", split="train")
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```
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