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 pytorch_model.bin from CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-mix-did-madar-corpus26/resolve/main/pytorch_model.bin
436 MB
- Xet hash:
- f3c3eadf6b48c9d5dd010e8d4ef962b6aa6898e9af99c146368aaa247f1987fb
- Size of remote file:
- 436 MB
- SHA256:
- 13993e45dfaa873d0e5d7bae7a92fded87bf6539c9ae8c10e4575097df07985e
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