Instructions to use natdebandi/beto_hate_speech_ar_bin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use natdebandi/beto_hate_speech_ar_bin with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="natdebandi/beto_hate_speech_ar_bin")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("natdebandi/beto_hate_speech_ar_bin") model = AutoModelForSequenceClassification.from_pretrained("natdebandi/beto_hate_speech_ar_bin") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba841f9ec65033221811533d1c18665ccc97a9c36bd7cc23410cfff9ac79b8a4
- Size of remote file:
- 5.24 kB
- SHA256:
- 8a7af3f96670c4719d4f1cd8e1d31b32b06ef0454b45db3735e42bf7065c787e
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