Instructions to use M47Labs/arabert_multiclass_news with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use M47Labs/arabert_multiclass_news with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="M47Labs/arabert_multiclass_news")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("M47Labs/arabert_multiclass_news") model = AutoModelForSequenceClassification.from_pretrained("M47Labs/arabert_multiclass_news", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- adc1fa9b1500a862005cbbb53c914657372c2e07670ecd9b6df5208917064718
- Size of remote file:
- 443 MB
- SHA256:
- 43585ff097af841ddf39a4a60cff965678b12150ce8dddbea857e0ee21664a31
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