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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("markusbayer/CySecBERT") model = AutoModelForMaskedLM.from_pretrained("markusbayer/CySecBERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from markusbayer/CySecBERT: direct link, hf CLI and curl.
- Browser
- Download file 112 Bytes
-
https://huggingface.co/markusbayer/CySecBERT/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://markusbayer/CySecBERT/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/markusbayer/CySecBERT/resolve/main/special_tokens_map.json
112 Bytes
| {"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"} |