Instructions to use facebook/roberta-hate-speech-dynabench-r4-target with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/roberta-hate-speech-dynabench-r4-target with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="facebook/roberta-hate-speech-dynabench-r4-target")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("facebook/roberta-hate-speech-dynabench-r4-target") model = AutoModelForSequenceClassification.from_pretrained("facebook/roberta-hate-speech-dynabench-r4-target", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea8ead1cdf2ff7da57d8c5802e42e0621495214504fade4ed431cf30bf67f834
- Size of remote file:
- 499 MB
- SHA256:
- 772c0df34d14a88d2e212272794407d079730fae6b313b05c14396d1cad389ad
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