Instructions to use ehsanaghaei/SecureBERT_Plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ehsanaghaei/SecureBERT_Plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ehsanaghaei/SecureBERT_Plus")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ehsanaghaei/SecureBERT_Plus") model = AutoModelForMaskedLM.from_pretrained("ehsanaghaei/SecureBERT_Plus") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6b47376a3a754eec739e808b72d1e063f2e3c7a2df2b254ea30fd09e148dc268
- Size of remote file:
- 627 Bytes
- SHA256:
- 343afb5ea3ddd39f245d7cb98b52e32b8f047a30e7578c8807aa9537f135c9c0
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