This is a RoBERTa-large model trained on 154M tweets until the end of December 2022 and finetuned for sentiment analysis (target based) on the
TweetSentiment
dataset of
SuperTweetEval
.
The original Twitter-based RoBERTa model can be found
here
.
from transformers import pipeline
text= 'If I make a game as a #windows10 Universal App. Will #xboxone owners be able to download and play it in November? @user @microsoft'
target = "@microsoft"
text_input = f"{text} </s> {target}"
pipe = pipeline('text-classification', model="cardiffnlp/twitter-roberta-large-topic-sentiment-latest")
pipe(text)
>> [{'label': 'negative or neutral', 'score': 0.8927537798881531}]
@inproceedings{antypas2023supertweeteval,
title={SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research},
author={Dimosthenis Antypas and Asahi Ushio and Francesco Barbieri and Leonardo Neves and Kiamehr Rezaee and Luis Espinosa-Anke and Jiaxin Pei and Jose Camacho-Collados},
booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
year={2023}
}
Runs of cardiffnlp twitter-roberta-large-topic-sentiment-latest on huggingface.co
422
Total runs
0
24-hour runs
-15
3-day runs
-43
7-day runs
-43
30-day runs
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