Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use mariadg/AttackVectorClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mariadg/AttackVectorClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mariadg/AttackVectorClassifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mariadg/AttackVectorClassifier") model = AutoModelForSequenceClassification.from_pretrained("mariadg/AttackVectorClassifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2f8ae11cf5ca6647beb0feae7bd9145ec9a593dba0f9d69a1f8d9470d957150b
- Size of remote file:
- 5.2 kB
- SHA256:
- fea6b0f9bdf5ea6ac066e8cf19ce0d20cd9e62c216b0b4b928ce53acee686a4a
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