Fill-Mask
Transformers
Safetensors
Arabic
English
bert
arabic
english
encoder
bilingual
mlm
tiny-model
from-scratch
Instructions to use oddadmix/Nawah-BERT-6M-bilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oddadmix/Nawah-BERT-6M-bilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="oddadmix/Nawah-BERT-6M-bilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("oddadmix/Nawah-BERT-6M-bilingual") model = AutoModelForMaskedLM.from_pretrained("oddadmix/Nawah-BERT-6M-bilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 401308478db51fb0082b9e915cb63f8a6b1954eba8fa539ad72e75350f5be9f5
- Size of remote file:
- 24 MB
- SHA256:
- aebf7394e8627462213604fbe95d07808ccd40b4068bf48f16ee2b96ae4a82fa
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