Token Classification
Transformers
TensorBoard
Safetensors
English
modernbert
ner
cybersecurity
threat-intelligence
secureBert
Instructions to use attack-vector/SecureModernBERT-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use attack-vector/SecureModernBERT-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="attack-vector/SecureModernBERT-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("attack-vector/SecureModernBERT-NER") model = AutoModelForTokenClassification.from_pretrained("attack-vector/SecureModernBERT-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f491b756299d3403ecadbc8cdde42f7a0d6293761308bee3ebd416cd1094ea5
- Size of remote file:
- 3.17 GB
- SHA256:
- 355db5828e53dad3fb07dfb9d1e869ab4a33eaa748de5119b7f93eef9127cfb5
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