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:
- cf77496e0cb5e9d35e9403ae72128ffe33e15332a2c95b01d0f7f3d16535aae2
- Size of remote file:
- 5.37 kB
- SHA256:
- bc7181b00303f72cd9e8d7e9489278da1dba68ace8042efb585819e98f131563
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