Instructions to use asafaya/albert-xlarge-arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asafaya/albert-xlarge-arabic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="asafaya/albert-xlarge-arabic")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("asafaya/albert-xlarge-arabic") model = AutoModelForMaskedLM.from_pretrained("asafaya/albert-xlarge-arabic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- daf449dfcd1aab1420054bb888afeefe6330e7c63cc25b7376dae6eeeff1c2cc
- Size of remote file:
- 860 kB
- SHA256:
- 40f25b5aae5c42a4089292e6616f37bca7b5a4f08608678b16ba5a55c9f050d7
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