Instructions to use Cyber-ThreaD/SecBERT-AttackER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cyber-ThreaD/SecBERT-AttackER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Cyber-ThreaD/SecBERT-AttackER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Cyber-ThreaD/SecBERT-AttackER") model = AutoModelForTokenClassification.from_pretrained("Cyber-ThreaD/SecBERT-AttackER") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2826d423308f60b873581ee924e1c4bb8759118705c3ba0bf7b52ec90fa586b2
- Size of remote file:
- 4.66 kB
- SHA256:
- a01377110804395519c90d1af4fb5afeb3515f17bf7f70061a6fd4c723c59944
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