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twitter-roberta-base-jun2022_sem_eval_2018_task_1
maxpe/twitter-roberta-base-jun2022_sem_eval_2018_task_1
twitter-roberta-base-jun2022_sem_eval_2018_task_1 is a text classification model from maxpe. Use it when you need a label for a piece of text. It is set up for transformers.
This model was trained on ~7000 tweets in English annotated for 11 emotion categories in SemEval-2018 Task 1: Affect in Tweets: SubTask 5: Emotion Classification (also available on the Hugging Face Dataset Hub).
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Aug 30, 2022
- Updated
- Aug 30, 2022
- SHA
- a3342502
Try a prompt
Model card
From the Hugging Face model README
Twitter-roBERTa-base-jun2022_sem_eval_2018_task1
This model was trained on ~7000 tweets in English annotated for 11 emotion categories in SemEval-2018 Task 1: Affect in Tweets: SubTask 5: Emotion Classification (also available on the Hugging Face Dataset Hub).
The underlying model is a RoBERTa-base model trained on 132.26M tweets until the end of June 2022. Fore more details check out the model page.
To quickly test it locally, use a pipeline:
from transformers import pipeline
pipe = pipeline("text-classification",model="maxpe/twitter-roberta-base-jun2022_sem_eval_2018_task_1")
pipe("I couldn't see any seafood for a year after I went to that restaurant that they send all the tourists to!",top_k=11)
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Aug 30, 2022
- Updated
- Aug 30, 2022