Fill-Mask
Transformers
PyTorch
Safetensors
English
bert
Cybersecurity
Cyber Security
Information Security
Computer Science
Cyber Threats
Vulnerabilities
Vulnerability
Malware
Attacks
Instructions to use markusbayer/CySecBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use markusbayer/CySecBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="markusbayer/CySecBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("markusbayer/CySecBERT") model = AutoModelForMaskedLM.from_pretrained("markusbayer/CySecBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 52e07d0c52880c62dd0114a1835b776457ec1f47b7b43551336f886d109f81d8
- Size of remote file:
- 2.86 kB
- SHA256:
- 7e0deae9126bd79506e8b0520a5d66142d3459e508ce47fe167f9c3ed85870e8
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