datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
natural-language-satisfiability@misc{https://doi.org/10.48550/arxiv.2211.05417,
doi = {10.48550/ARXIV.2211.05417},
url = {https://arxiv.org/abs/2211.05417},
author = {Schlegel, Viktor and Pavlov, Kamen V. and Pratt-Hartmann, Ian},
keywords = {Computation and Language (cs.CL), Artificial Intelligence (cs.AI), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Can Transformers Reason in Fragments of Natural Language?},
publisher = {arXiv},
year = {2022},
copyright =… See the full description on the dataset page: https://huggingface.co/datasets/tasksource/natural-language-satisfiability.natural_language_to_linux
nl2linux
This a custom dataset used to fine-tune Large Language Models for Linux Command Generation.
The dataset is created by filtering AnishJoshi/nl2bash-custom dataset from huggingface.
Dataset Structure
train.json: Training split.
dev.json: Development split.
test.json: Test split.
Usage
from datasets import load_dataset
dataset = load_dataset("prabhanshubhowal/natural_language_to_linux")
Features
'nl_command': The natural language… See the full description on the dataset page: https://huggingface.co/datasets/prabhanshubhowal/natural_language_to_linux.MathMinos-Natural-language-feedback
Dataset Card for Math-Minos
Project Page: https://github.com/KbsdJames/MATH-Minos
Paper: https://arxiv.org/abs/2406.14024
Info: This dataset contains the natural language feedback used during the first training phase of Math-Minos. It includes step-by-step natural language feedback from GPT-4 for given problems and solutions, supplementing the traditional ORM/PRM training.
Data Loading
from datasets import load_dataset
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/KbsdJames/MathMinos-Natural-language-feedback.ai-natural-language-tests
NL-to-Test Training Dataset
Training data for fine-tuning a code model that generates Cypress and Playwright
end-to-end tests from natural-language requirements.
Each example is a chat pair: a user message containing a plain-English test requirement
and target URL, and an assistant message containing a complete, runnable test file that
follows the conventions of the AI Natural Language Tests
platform. Playwright examples embed a top-level testData object with a resolveLocator… See the full description on the dataset page: https://huggingface.co/datasets/aiqualitylab/ai-natural-language-tests.natural_language_classifier
How-to
from datasets import load_dataset
dataset = load_dataset("aushakova/natural_language_classifier", "main")