Text Classification
Transformers
PyTorch
English
roberta
text classification
hate speech
offensive language
hatecheck
text-embeddings-inference
Instructions to use henrystoll/hatespeech-refugees with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henrystoll/hatespeech-refugees with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henrystoll/hatespeech-refugees")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henrystoll/hatespeech-refugees") model = AutoModelForSequenceClassification.from_pretrained("henrystoll/hatespeech-refugees", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 59c8e94652cb58e028031c62da97c39c59c24000269859dbd3dba91b0a2060a6
- Size of remote file:
- 499 MB
- SHA256:
- 53665af5a4f1a98622efb8141bea03e05fc525cd6887b284e07f28befba37a37
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