Instructions to use T0KII/MASRIBERTV4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use T0KII/MASRIBERTV4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="T0KII/MASRIBERTV4")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("T0KII/MASRIBERTV4") model = AutoModelForMaskedLM.from_pretrained("T0KII/MASRIBERTV4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 86d956bb6b2f8cad9c06641b8b8c73802f216b8eb93fff84afd2d1f0a7b0cf47
- Size of remote file:
- 1.92 GB
- SHA256:
- a36b09de8553e1e5b08d8e3b2e1e5a39e188a2d1ff5c175a231bca476a13f80f
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