Jeopardy questions from Mosaic Gauntlet

Sourced from https://github.com/mosaicml/llm-foundry/blob/main/scripts/eval/local_data/world_knowledge/jeopardy_all.jsonl

Description: Jeopardy consists of 2,117 Jeopardy questions separated into 5 categories: Literature, American History, World History, Word Origins, and Science. The model is expected to give the exact correct response to the question. It was custom curated by MosaicML from a larger Jeopardy set available on Huggingface.

How to use

from datasets import load_dataset

dataset = load_dataset("soldni/jeopardy", "mosaicml_gauntlet")
model = ...
tokenizer = ...

# Given context, try to predict the continuation
for row in dataset:
    input_ids = tokenizer(row['context'], return_tensors='pt').to(model.device)
    outputs = model.generate(input_ids, max_new_tokens=100)
    decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
    correct = row['continuation'] in decoded
    print("Gold:", row['continuation'])
    print("Pred:", decoded)
    print("Correct?", correct)
    print("----")