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--- |
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license: apache-2.0 |
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task_categories: |
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- question-answering |
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- conversational |
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language: |
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- en |
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tags: |
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- evaluation |
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pretty_name: MT Bench |
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size_categories: |
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- n<1K |
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--- |
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# MT Bench by LMSYS |
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This set of evaluation prompts is created by the [LMSYS org](https://huggingface.co/lmsys) for better evaluation of chat models. |
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For more information, see the [paper](https://arxiv.org/abs/2306.05685). |
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### Dataset loading |
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To load this dataset, use 🤗 datasets: |
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```python |
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from datasets import load_dataset |
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data = load_dataset(HuggingFaceH4/mt_bench_prompts, split="train") |
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``` |
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### Dataset creation |
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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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``` |
