Instructions to use PaulAdversarial/T5_PAN_Hate_Speech_Twitter_topic_author_ishatespeach with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PaulAdversarial/T5_PAN_Hate_Speech_Twitter_topic_author_ishatespeach with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("PaulAdversarial/T5_PAN_Hate_Speech_Twitter_topic_author_ishatespeach") model = AutoModelForMultimodalLM.from_pretrained("PaulAdversarial/T5_PAN_Hate_Speech_Twitter_topic_author_ishatespeach") - Notebooks
- Google Colab
- Kaggle
Quick Links
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Check out the documentation for more information.
##A T5ForConditionalGeneration trained on 3 tasks from PAN Profiling Hate Speech Spreaders on Twitter dataset (EN):
- author attribution (train and test sets from the PAN task)
- topic attribution - topics were assigned with BertTopic library using embeddings from
cardiffnlp/bertweet-base-hateRoberta model (train and test sets from the PAN task) - hate speech identification (train set from the PAN task)
in order to generate tone of comment use prefix hater classification:
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# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("PaulAdversarial/T5_PAN_Hate_Speech_Twitter_topic_author_ishatespeach") model = AutoModelForMultimodalLM.from_pretrained("PaulAdversarial/T5_PAN_Hate_Speech_Twitter_topic_author_ishatespeach")