paraphrase
jitteredwebsites-merged-224-paraphrasedru_paraphraser
Dataset Card for ParaPhraser
Dataset Summary
ParaPhraser is a news headlines corpus annotated according to the following schema:
1: precise paraphrases
0: near paraphrases
-1: non-paraphrases
The Plus part is also available.
It contains clusters of news headline paraphrases labeled automatically by a fine-tuned paraphrase detection BERT model.In order to load it:
from datasets import load_dataset
corpus = load_dataset('merionum/ru_paraphraser', data_files='plus.jsonl')… See the full description on the dataset page: https://huggingface.co/datasets/merionum/ru_paraphraser.chatgpt-paraphrasesThis is a dataset of paraphrases created by ChatGPT.
Model based on this dataset is avaible: model
We used this prompt to generate paraphrases
Generate 5 similar paraphrases for this question, show it like a numbered list without commentaries: {text}
This dataset is based on the Quora paraphrase question, texts from the SQUAD 2.0 and the CNN news dataset.
We generated 5 paraphrases for each sample, totally this dataset has about 420k data rows. You can make 30 rows from a row from… See the full description on the dataset page: https://huggingface.co/datasets/humarin/chatgpt-paraphrases.harvest_apples_with_agilex_piper_sim_ee_paraphrases20This dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 25,
"features": {
"observation.state": {
"dtype": "float32",
"fps": 25,
"shape": [
8
],
"names": [
"ee.x",
"ee.y",
"ee.z",
"ee.roll",
"ee.pitch",
"ee.yaw"… See the full description on the dataset page: https://huggingface.co/datasets/Faless/harvest_apples_with_agilex_piper_sim_ee_paraphrases20.paraphrase-qa日本語Wikipedia中のテキストを元に言い換えを生成し、その言い換えを元にクエリと回答をLLMに生成させたデータセットです。
出力にライセンス的な制約があるモデルを利用していないことと、元データとして日本語Wikipediaを利用していることから、CC-BY-SA 4.0ライセンスのもとでの配布とします。
turku_paraphrase_corpusTurku Paraphrase Corpus is a dataset of 104,645 manually annotated Finnish paraphrases. The vast majority of the data is classified as a paraphrase either in the given context, or universally.