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")# pip install -U transformers accelerate # 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
Download pytorch_model.bin from ehsanaghaei/SecureBERT_Plus: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/ehsanaghaei/SecureBERT_Plus/resolve/refs%2Fpr%2F4/pytorch_model.bin
- Command line
-
hf download hf://ehsanaghaei/SecureBERT_Plus@refs/pr/4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ehsanaghaei/SecureBERT_Plus/resolve/refs%2Fpr%2F4/pytorch_model.bin
499 MB
- Xet hash:
- 30a1e9e2b51dc936db0158e586063518280f0ecece6f594620446165868e259c
- Size of remote file:
- 499 MB
- SHA256:
- 2cbb2e40b64410a338ee331251b96dc603646ec5262117c6208d5881e6e1f8e4
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