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:
- d1e563f93f9d75026a3f18a064aab2d236c9eff5b991182a9eaf28f01867e851
- Size of remote file:
- 1.92 GB
- SHA256:
- 70c6489f0d20d83629bbab2c806fd90d4114c1c4aaf22a5018d8654a7aede744
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