Text Classification
Transformers
Safetensors
English
roberta
security
vulnerability
cve
mitre-attack
cti
multi-label-classification
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use CIRCL/vulnerability-attack-technique-classification-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIRCL/vulnerability-attack-technique-classification-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CIRCL/vulnerability-attack-technique-classification-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CIRCL/vulnerability-attack-technique-classification-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("CIRCL/vulnerability-attack-technique-classification-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from CIRCL/vulnerability-attack-technique-classification-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/CIRCL/vulnerability-attack-technique-classification-roberta-base/resolve/main/model.safetensors
- Command line
-
hf download hf://CIRCL/vulnerability-attack-technique-classification-roberta-base/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/CIRCL/vulnerability-attack-technique-classification-roberta-base/resolve/main/model.safetensors
499 MB
- Xet hash:
- c1ea0fb14a3d2447bc842c573720c40c1b6e77943d8580faade9935dc29e2b4e
- Size of remote file:
- 499 MB
- SHA256:
- 606be348b506ba31c823ef630add2e23e972ea916207c4e85e9c843bb0186f6f
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