Instructions to use ehsanaghaei/SecureBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ehsanaghaei/SecureBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ehsanaghaei/SecureBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ehsanaghaei/SecureBERT") model = AutoModelForMaskedLM.from_pretrained("ehsanaghaei/SecureBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b44099ade116cc361e6aa5379c18f0457aff764daa8c04ebefef29cbe9f593c
- Size of remote file:
- 499 MB
- SHA256:
- e0b5108e88957e7524dd1eb3dc4ed772275c2df7362840903df8cdb7750bb238
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.