Text Classification
Transformers
Safetensors
English
roberta
cybersecurity
pentesting
phase-detection
Eval Results (legacy)
text-embeddings-inference
Instructions to use MattP30098638/PenTest-AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MattP30098638/PenTest-AI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MattP30098638/PenTest-AI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MattP30098638/PenTest-AI") model = AutoModelForSequenceClassification.from_pretrained("MattP30098638/PenTest-AI") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c98ee61072627e6e91c038c348a7799550f1c9fc72f0270515fb16647cc7440
- Size of remote file:
- 672 Bytes
- SHA256:
- a21f56bb1fb9c80d5d6773d6a6742cf685885b74f125b9d3be39572c32cb2cc9
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