datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Feedback-Collection
Dataset Card
Dataset Summary
The Feedback Collection is a dataset designed to induce fine-grained evaluation capabilities into language models.\
Recently, proprietary LLMs (e.g., GPT-4) have been used to evaluate long-form responses. In our experiments, we found that open-source LMs are not capable of evaluating long-form responses, showing low correlation with both human evaluators and GPT-4.\
In our paper, we found that by (1) fine-tuning feedback generated by GPT-4… See the full description on the dataset page: https://huggingface.co/datasets/prometheus-eval/Feedback-Collection.wb-feedbacks
Dataset Card for Wildberries products
Dataset Summary
The dataset contains product reviews from the Russian marketplace Wildberries, collected by mining about The dataset was collected by bruteforcing possible product identifiers (about 230 million) and querying all available feedbacks for them. The data are stored in zstd-archives containing jsonl-files. The 'nmId' in the dataset usually corresponds to the valid product article on the site, but sometimes reviews are… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/wb-feedbacks.Code-Feedback-decontaminationA decontaminated version of m-a-p/Code-Feedback.
The excluded (28) files are "contaminated" with only two code segments:
simple GCD function: while b: a, b = b, a % b return a
sum_to_n solution: return sum(range(n + 1))
And reformated to sharegpt.
Decontamination is done in the same way as Magicoder (ie., bigcode decontamination process), which uses a substring-match-finding method to find overlaps between a target dataset and the following standard benchmarks:
HumanEval
MBPP… See the full description on the dataset page: https://huggingface.co/datasets/Leon-Leee/Code-Feedback-decontamination.ultra-feedback-js-instruct
Ultra Feedback JS Instruct
A subset of the wonderful and elegant Ultra Feedback dataset. Ratings are 1-5 ( inclusive )
Generation Notebook
Example
{
"inst": "Refine the subsequent JavaScript code snippet to obtain the cumulative total of elements within an array:\nlet numbers = [1, 2, 3]",
"author": "codellama-34b-instruct",
"fun": "let numbers = [1, 2, 3];\nlet total = numbers.reduce((a, b) => a + b);\nconsole.log(total); // Output: 6",
"rating": "5"
}