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
Ehsan Aghaei commited on
Commit ·
1763c0a
1
Parent(s): ad21ec9
Create README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# SecureBERT: A Domain-Specific Language Model for Cybersecurity
|
| 2 |
+
SecureBERT is a domain-specific language model based on RoBERTa which is trained on a huge amount of cybersecurity data and fine-tuned/tweaked to understand/represent cybersecurity textual data.
|
| 3 |
+
|
| 4 |
+
# Reference
|
| 5 |
+
Use the paper below to cite our work.
|
| 6 |
+
https://arxiv.org/pdf/2204.02685
|
| 7 |
+
|
| 8 |
+
** The paper has been accepted in "EAI SecureComm 2022 - 18th EAI International Conference on Security and Privacy in Communication Networks".
|