Instructions to use CyberPeace-Institute/Cybersecurity-Knowledge-Graph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CyberPeace-Institute/Cybersecurity-Knowledge-Graph with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="CyberPeace-Institute/Cybersecurity-Knowledge-Graph", trust_remote_code=True)# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("CyberPeace-Institute/Cybersecurity-Knowledge-Graph", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84d1d3c929d263c3552c3fc2b1c5201f8fe24adda402888285c27d16cd6be36c
- Size of remote file:
- 499 MB
- SHA256:
- e6147a98aa2baaa545903103e9e2f0e55fc249ec638cfe27e273ffdd247479c4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.