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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d0dfa1928012cb7bebd20b7b0b63a65c11b65eb33ffd8b6920889a7d2f04a67
- Size of remote file:
- 3.96 kB
- SHA256:
- 099b9c556d73a3ad800295eb246d8e5605493d8ded30e8e7169acd7aeaf5dec3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.