Fill-Mask
Transformers
PyTorch
Safetensors
English
bert
exbert
security
cybersecurity
cyber security
threat hunting
threat intelligence
Instructions to use jackaduma/SecBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jackaduma/SecBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jackaduma/SecBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jackaduma/SecBERT") model = AutoModelForMaskedLM.from_pretrained("jackaduma/SecBERT") - Inference
- Notebooks
- Google Colab
- Kaggle
Kun Ma commited on
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* [`SecBERT`](https://huggingface.co/jackaduma/SecBERT)
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* [`SecRoBERTa`](https://huggingface.co/jackaduma/SecRoBERTa)
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The original repo can be found [here](https://github.com/jackaduma/SecBERT).
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* [`SecBERT`](https://huggingface.co/jackaduma/SecBERT)
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* [`SecRoBERTa`](https://huggingface.co/jackaduma/SecRoBERTa)
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---
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## **Fill Mask**
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We proposed to build language model which work on cyber security text, as result, it can improve downstream tasks (NER, Text Classification, Semantic Understand, Q&A) in Cyber Security Domain.
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First, as below shows Fill-Mask pipeline in [Google Bert](), [AllenAI SciBert](https://github.com/allenai/scibert) and our [SecBERT](https://github.com/jackaduma/SecBERT) .
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<img src="./fill-mask-result.png" width="150%" height="150%">
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---
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The original repo can be found [here](https://github.com/jackaduma/SecBERT).
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fill-mask-result.png
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