Instructions to use moha/mbert_ar_c19 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use moha/mbert_ar_c19 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="moha/mbert_ar_c19")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("moha/mbert_ar_c19") model = AutoModelForMaskedLM.from_pretrained("moha/mbert_ar_c19", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb8f0ad175219de6a4f92f553958ad8473d5d4b2c657a2d639af43e1014a0e83
- Size of remote file:
- 670 MB
- SHA256:
- 6db5e5d5ce31ec79586285a845329245bea9f32d64e0159425993c71cb26f680
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