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:
- dd869ddf7df2546b9db4712eedb707970517562bdf281fb7ea454c6e82e5489c
- Size of remote file:
- 1.39 kB
- SHA256:
- 76140491bee99d35c545192620f87c95e7b4066640bb87bc815a7450d9f0ec42
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