Instructions to use AnonymousCS/BERT_hateval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnonymousCS/BERT_hateval with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnonymousCS/BERT_hateval")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnonymousCS/BERT_hateval") model = AutoModelForSequenceClassification.from_pretrained("AnonymousCS/BERT_hateval") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1e1a900ff251fd86f3178b9fb028e089542582d19c1455f73db3ed717caffa8
- Size of remote file:
- 438 MB
- SHA256:
- 956bd62bfa09ef7da4373f1e8af0b28b2c2b352f8c7c3b8c05819e2b4a1619e6
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