Sentence Similarity
Transformers
PyTorch
mpnet
feature-extraction
cybersecurity
sentence-embedding
text-embeddings-inference
Instructions to use basel/ATTACK-BERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basel/ATTACK-BERT with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("basel/ATTACK-BERT") model = AutoModel.from_pretrained("basel/ATTACK-BERT") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1216beb0aa2698a64781907d2faf5438d3b893642363b6725be5c59be2a9cc06
- Size of remote file:
- 438 MB
- SHA256:
- 4060a0bfecefa4b7afe028f7e4318d6f522e77f53b2842edc81e29f657acafa0
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