Instructions to use asafaya/bert-medium-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asafaya/bert-medium-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="asafaya/bert-medium-arabic")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("asafaya/bert-medium-arabic") model = AutoModelForMaskedLM.from_pretrained("asafaya/bert-medium-arabic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2850acf7926cce0103111bb8f43f4c685101783b06bc8245b2bc9161e526026b
- Size of remote file:
- 170 MB
- SHA256:
- 9cf23c0016b4f586788f1430a3bc4aaad5175b86fed37256db9a3dfc94503524
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