Instructions to use poison-attack/t5large-hate_speech_badnet_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poison-attack/t5large-hate_speech_badnet_0 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("poison-attack/t5large-hate_speech_badnet_0") model = AutoModelForSeq2SeqLM.from_pretrained("poison-attack/t5large-hate_speech_badnet_0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15394744ef13f04f41b058379df9e868c76f660f1e93e92149c732b7d211f260
- Size of remote file:
- 3.13 GB
- SHA256:
- 74e090e8b473c5a401e84e5a90ac08fcd11df9276f05675d5161045281243a56
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