Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi") model = AutoModelForSequenceClassification.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-mix-did-nadi") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c3e0fe3aef3580c7e9f379aa7e3a70644f06edb66937edbf13f194fc2950636c
- Size of remote file:
- 436 MB
- SHA256:
- 536809cb29d1416e0ae34b27e11d15718c9414fa325157f31eda31d7132723b5
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