Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26 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-madar-corpus26 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-madar-corpus26")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26") model = AutoModelForSequenceClassification.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26: direct link, hf CLI and curl.
- Browser
- Download file 1.4 kB
-
https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26/resolve/main/training_args.bin
- Command line
-
hf download hf://CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26/resolve/main/training_args.bin
1.4 kB
- Xet hash:
- 41cff17a898b4762d5118cb6af0a62b48dfcd8a4a62c7ed6f9843e86fe1023c1
- Size of remote file:
- 1.4 kB
- SHA256:
- 939f5f588e71b04f86d857acccd25cc371f2b4a9903387e4b81c4e199f8f59d8
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