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:
- 22b35b05c5cfe28ed310524f5db9897e5f12eaf226069ab117a1b8614c717b0a
- Size of remote file:
- 1.35 kB
- SHA256:
- 7c6bc5b1cb495788346b3ae0f62cf65a98096fb57dfbe51877a30a569688bcd6
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