Fill-Mask
Transformers
PyTorch
Safetensors
English
roberta
exbert
security
cybersecurity
cyber security
threat hunting
threat intelligence
Instructions to use jackaduma/SecRoBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jackaduma/SecRoBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jackaduma/SecRoBERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jackaduma/SecRoBERTa") model = AutoModelForMaskedLM.from_pretrained("jackaduma/SecRoBERTa") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cff1bba324d941dbcdae22db76453d467627e1fe386e72113fc9868f02f2cddb
- Size of remote file:
- 336 MB
- SHA256:
- fdae22fea29de7cf62be533474b5033294eb0d9b6bd6437dbd3757053468706b
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