Instructions to use huzaifas-sidhpurwala/secbert-redhat-data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huzaifas-sidhpurwala/secbert-redhat-data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="huzaifas-sidhpurwala/secbert-redhat-data")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("huzaifas-sidhpurwala/secbert-redhat-data") model = AutoModelForSequenceClassification.from_pretrained("huzaifas-sidhpurwala/secbert-redhat-data") - Notebooks
- Google Colab
- Kaggle
secbert-redhat-data
This is a fine-tuned secbert model, using Red Hat public security data from: https://huggingface.co/datasets/huzaifas-sidhpurwala/RedHat-security-VeX
Model Details
Model Description
- Developed by: Huzaifa Sidhpurwala huzaifas@redhat.com
- Model type: Text classification
- License: Apache 2.0
Highlights
This model is trained with the summary, description and severity fields from https://huggingface.co/datasets/huzaifas-sidhpurwala/RedHat-security-VeX
The aim here is given the description of a security issue, the model should correct be able to estimate the severity level of the security issue in accordance with the standards documented at: https://access.redhat.com/security/updates/classification
How to Get Started with the Model
A minimal inference code is available at: https://github.com/sidhpurwala-huzaifa/redhat-sev-classifier/blob/main/inference/
Model Card Contact
Huzaifa Sidhpurwala - huzaifas@redhat.com
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Model tree for huzaifas-sidhpurwala/secbert-redhat-data
Base model
jackaduma/SecBERT