Datasets:

Lots-of-LoRAs
/

task285_imdb_answer_generation

input stringlengths 3.81k 13.8k	output sequencelengths 1 1	id stringlengths 40 40
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-209578af37de40b9b94f21bd902ee444
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-ff6b485d2c0b4529bce4deead9c13ad6
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-08f960f4b4974ea395e6793191e5bac6
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-f05d2f01398a4fd5883a00a9f09ec3bb
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-d7500dc47c0e42369f8b9bb87adab730
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-78f27018314348efae44f71249faf3d9
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-e5a22cac125b420ca6a0889dd4fd64e5
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-d2bb3a21ad044be1a7beb8ae2e5f2317
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-b82f1f56631f4bbab6092a6073698640
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-feb5bfbe4a5c47199e693844c77df909
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-6f2438f097424da0bb32634e1d0973b1
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-bc64dcc6d8084f2e9185da5444093503
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-250d9c76980d4ef390004087c4de66f9
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-633c266ca014452c9917e013bc37ce12
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-8f1a88b191504c25ab4f894ea6ca8111
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-4edb389057b44a2b8bd1fc72bca6dfbf
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-da6cf473ba3e4a09abbd9a29c69f03a4
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-904f6dbde98a4099b5868528860e500c
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-146458d2a55c4aaeaee0b6df719164c6
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-4ca49395ee944e4ea1033f3dda855b13
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-a12bd4b30d224907a1935d5d6f4e6f35
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-252adab0413a43e2b80f36f28fb8c00d
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-430f1d89d8c24db8b331032abc603a6b
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-700ec2db72db47daad1c2416699fc9fb
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-c5a07faebc084d39b0a2fb63fd665ac3
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-d707cf7e7d6845f68c58c13b6019e368
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-346053e0124649d29ca9a95a8f5d7f8e
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-421416f59f6843a0a8a20b2f7ce901b9
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-7790e6a981354f819da2f8f71943d1e3
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-dbf7d87cbbb74edc9cd77c30a151d42e
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-3e1bdd9e4cc148cd9f687829f985ac41
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-44b3b15e16f64e5d9149aebbea6456a7
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-a2433248ab79461b97663f9af9171fb5
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-cf477d764a4c4559916e4b18899c7ade
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-7818851e5c094c3cb9eb124381c7fdd4
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-e02731444773422f837b198c6cf71c0a
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "yes" ]	task285-684184bea0b646b0aab1f48d7c606ed3
Definition: In this task, you are given a review of a movie and a boolean question whether this review has positive sentiment or negative sentiment. Your task is to generate answer "yes" when the tweet has that particular sentiment, otherwise generate answer "no". Positive Example 1 - Input: Review: For a movie that g...	[ "no" ]	task285-d5f376a4f0a54a4884fd843825dafc69

End of preview. Expand in Data Studio

Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task285_imdb_answer_generation

Additional Information

Citation Information

The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:

@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
    title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}, 
    author={Yizhong Wang and Swaroop Mishra and Pegah Alipoormolabashi and Yeganeh Kordi and Amirreza Mirzaei and Anjana Arunkumar and Arjun Ashok and Arut Selvan Dhanasekaran and Atharva Naik and David Stap and Eshaan Pathak and Giannis Karamanolakis and Haizhi Gary Lai and Ishan Purohit and Ishani Mondal and Jacob Anderson and Kirby Kuznia and Krima Doshi and Maitreya Patel and Kuntal Kumar Pal and Mehrad Moradshahi and Mihir Parmar and Mirali Purohit and Neeraj Varshney and Phani Rohitha Kaza and Pulkit Verma and Ravsehaj Singh Puri and Rushang Karia and Shailaja Keyur Sampat and Savan Doshi and Siddhartha Mishra and Sujan Reddy and Sumanta Patro and Tanay Dixit and Xudong Shen and Chitta Baral and Yejin Choi and Noah A. Smith and Hannaneh Hajishirzi and Daniel Khashabi},
    year={2022},
    eprint={2204.07705},
    archivePrefix={arXiv},
    primaryClass={cs.CL},
    url={https://arxiv.org/abs/2204.07705}, 
}

More details can also be found in the following paper:

@misc{brüelgabrielsson2024compressserveservingthousands,
    title={Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead}, 
    author={Rickard Brüel-Gabrielsson and Jiacheng Zhu and Onkar Bhardwaj and Leshem Choshen and Kristjan Greenewald and Mikhail Yurochkin and Justin Solomon},
    year={2024},
    eprint={2407.00066},
    archivePrefix={arXiv},
    primaryClass={cs.DC},
    url={https://arxiv.org/abs/2407.00066}, 
}