Instructions to use crcb/hateval_re with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crcb/hateval_re with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="crcb/hateval_re")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("crcb/hateval_re") model = AutoModelForSequenceClassification.from_pretrained("crcb/hateval_re", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3f1f8134c5f54ebee5816085875df246df2ffe7a1d76eea57eed3174217b880
- Size of remote file:
- 3.62 kB
- SHA256:
- b89aa2e6c76b7b9ed04fb3b93f4fc38c3285b53eb63d0d22dadcaa82a7743006
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