Instructions to use asafaya/bert-mini-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asafaya/bert-mini-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="asafaya/bert-mini-arabic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("asafaya/bert-mini-arabic") model = AutoModelForMaskedLM.from_pretrained("asafaya/bert-mini-arabic", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from asafaya/bert-mini-arabic: direct link, hf CLI and curl.
- Browser
- Download file 46.3 MB
-
https://huggingface.co/asafaya/bert-mini-arabic/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://asafaya/bert-mini-arabic/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/asafaya/bert-mini-arabic/resolve/main/flax_model.msgpack
46.3 MB
- Xet hash:
- 021918fc4339eee3dc091bc48447e267469e535629d8ed944d0c43ec1abe2a74
- Size of remote file:
- 46.3 MB
- SHA256:
- c7a16e14f0439d52b7af3b7e78f2b26e520d2d51156a627ab76f3a9e84c6d94e
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