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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb36addff25d9d08d0bf158836a86e1b84ecd5146a87fb8a1a5216f9186708b1
- Size of remote file:
- 499 MB
- SHA256:
- d261b08a989502ad1fb22291e646842831f926c57a3d56d81074af2ae6d40044
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.