Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-da 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-da with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="CAMeL-Lab/bert-base-arabic-camelbert-da")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-da") model = AutoModelForMaskedLM.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-da", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from CAMeL-Lab/bert-base-arabic-camelbert-da: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da/resolve/refs%2Fpr%2F3/flax_model.msgpack
- Command line
-
hf download hf://CAMeL-Lab/bert-base-arabic-camelbert-da@refs/pr/3/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da/resolve/refs%2Fpr%2F3/flax_model.msgpack
436 MB
- Xet hash:
- 4e73b1b42e7259553ae1fbd1b7aafaf3b3f67b2bc209e20ec3bc3028a86f6ab6
- Size of remote file:
- 436 MB
- SHA256:
- 588bca708c3688e69ac6a5e3a03a8d3459900e0487c295856e01ab51fb6f0701
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