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cardiffnlp/xlm-roberta-base-sentiment-multilingual
xlm-roberta-base-sentiment-multilingual is a text classification model from cardiffnlp. Use it when you need a label for a piece of text. It is set up for transformers.
This model is a fine-tuned version of xlm-roberta-base on the cardiffnlp/tweetsentimentmultilingual (all) via tweetnlp. Training split is train and parameters have been tuned on the validation split validation.
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From the Hugging Face model README
This model is a fine-tuned version of xlm-roberta-base on the
cardiffnlp/tweet_sentiment_multilingual (all)
via tweetnlp.
Training split is train and parameters have been tuned on the validation split validation.
Following metrics are achieved on the test split test (link).
Install tweetnlp via pip.
pip install tweetnlp
Load the model in python.
import tweetnlp
model = tweetnlp.Classifier("cardiffnlp/xlm-roberta-base-sentiment-multilingual", max_length=128)
model.predict('Get the all-analog Classic Vinyl Edition of "Takin Off" Album from {@herbiehancock@} via {@bluenoterecords@} link below {{URL}}')
@inproceedings{dimosthenis-etal-2022-twitter,
title = "{T}witter {T}opic {C}lassification",
author = "Antypas, Dimosthenis and
Ushio, Asahi and
Camacho-Collados, Jose and
Neves, Leonardo and
Silva, Vitor and
Barbieri, Francesco",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics"
}