Instructions to use T0KII/MASRIBERTv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use T0KII/MASRIBERTv3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="T0KII/MASRIBERTv3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("T0KII/MASRIBERTv3") model = AutoModelForMaskedLM.from_pretrained("T0KII/MASRIBERTv3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c96aa73110122391de4031f346ed40af62df09a8e40c26d597e71be91d04c1f8
- Size of remote file:
- 1.55 GB
- SHA256:
- ae09de78655ba24fcf06d47bccde06f0f4ed8e0cb16d95753d1e068eef30e5e9
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