Instructions to use faisalq/bert-medium-arapoembert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faisalq/bert-medium-arapoembert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="faisalq/bert-medium-arapoembert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("faisalq/bert-medium-arapoembert") model = AutoModelForMaskedLM.from_pretrained("faisalq/bert-medium-arapoembert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb0e67d771fec9c1f54b158b2a02bf3a865aa2d72ce603c6be7a5c476cc732a0
- Size of remote file:
- 383 MB
- SHA256:
- a5881ed374ee5a34da67ac23217630b4d18e727951b99fe89a87c62b69e65487
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