Feature Extraction
Transformers
Safetensors
English
mpnet
cybersecurity
classification
fine-tuned
text-embeddings-inference
Instructions to use selfconstruct3d/AttackGroup-MPNET with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use selfconstruct3d/AttackGroup-MPNET with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="selfconstruct3d/AttackGroup-MPNET")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("selfconstruct3d/AttackGroup-MPNET") model = AutoModel.from_pretrained("selfconstruct3d/AttackGroup-MPNET") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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print(f"Predicted GroupID: {predicted_class}")
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```
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Predicted GroupID: G0001
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## How to Get Started with the Model (Embeddings)
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print(f"Predicted GroupID: {predicted_class}")
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```
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Predicted GroupID: G0001
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https://attack.mitre.org/groups/G0001/
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## How to Get Started with the Model (Embeddings)
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