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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8980a89b7c4e52a49d6ab94aff84db816bb435113820cfef637b97d9a1a68301
- Size of remote file:
- 776 MB
- SHA256:
- 6966140456176554437ffa53e52f3ae13d84dd6fd92d37a2db68cc4b9e4c0cab
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