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Ebtihal/AraBertMo_base_V10
AraBertMo_base_V10 is a fill-mask model from Ebtihal. Use it when you need the model to fill a missing word. It is set up for transformers.
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From the Hugging Face model README
Arabic Model AraBertMo_base_V10
language: ar tags: Fill-Mask datasets: OSCAR widget:
AraBERTMo is an Arabic pre-trained language model based on Google's BERT architechture.
AraBERTMo_base uses the same BERT-Base config.
AraBERTMo_base now comes in 10 new variants
All models are available on the HuggingFace model page under the Ebtihal name.
Checkpoints are available in PyTorch formats.
`AraBertMo_base_V10' model was pre-trained on ~3 million words:
this model achieves the following results:
| Task | Num examples | Num Epochs | Batch Size | steps | Wall time | training loss |
|---|---|---|---|---|---|---|
| Fill-Mask | 30024 | 10 | 64 | 4700 | 9h 13m 43s | 7.2395 |
You can use this model by installing torch or tensorflow and Huggingface library transformers. And you can use it directly by initializing it like this:
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("Ebtihal/AraBertMo_base_V10")
model = AutoModelForMaskedLM.from_pretrained("Ebtihal/AraBertMo_base_V10")