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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b50c51192a923ee924d082baab1a8ed4cdaab0389a098f7f1c8689d2ba9914f
- Size of remote file:
- 2.84 GB
- SHA256:
- 525619790f42441378dea039f6451ab5b1409bb46b680a9eb9e1f63fff8ca8d1
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