Instructions to use surajp/SanBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use surajp/SanBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="surajp/SanBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("surajp/SanBERTa") model = AutoModelForMaskedLM.from_pretrained("surajp/SanBERTa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a2a1916db956655b7cf41aa564484587df02e11371e1d148f216dee5664b88f5
- Size of remote file:
- 265 MB
- SHA256:
- 172d685114761ec2b7bc9d939c8702b0601359022144ace81f877bc854b22080
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