Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use CIRCL/vulnerability-severity-classification-roberta-base-expC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIRCL/vulnerability-severity-classification-roberta-base-expC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CIRCL/vulnerability-severity-classification-roberta-base-expC")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CIRCL/vulnerability-severity-classification-roberta-base-expC") model = AutoModelForSequenceClassification.from_pretrained("CIRCL/vulnerability-severity-classification-roberta-base-expC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d4340cc3f1661f0bf120e4aa4352443303efbc22340630112da38352cb72a5e
- Size of remote file:
- 5.84 kB
- SHA256:
- b06a5d9c77218eead0f3ac5ae97fdbd961bae16429350842e0e22fc257d3a464
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.