Instructions to use CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth 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-eighth 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-msa-eighth")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth") model = AutoModelForMaskedLM.from_pretrained("CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth/resolve/refs%2Fpr%2F1/flax_model.msgpack
- Command line
-
hf download hf://CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth@refs/pr/1/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-msa-eighth/resolve/refs%2Fpr%2F1/flax_model.msgpack
436 MB
- Xet hash:
- 83a7124ec5c71a735a793467a98edb30bf72a230c7b3331c1f9f3922f96cc3f0
- Size of remote file:
- 436 MB
- SHA256:
- bde9b2fb827044d49d85fec869e4ed2d17e2fcbcc305662a25bd9b57667869bc
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