Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment 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-msa-sentiment 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-msa-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment") model = AutoModelForSequenceClassification.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa-sentiment") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d1e4fa4b2a14c20868c49c52c58c1713be348a6ce3c122aacefaba971627486
- Size of remote file:
- 436 MB
- SHA256:
- 543da83a6ae351ad8088f1649ada775981cf83567d970a6b1b2f13b70e21d7d4
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