Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
classification
nlp
vulnerability
text-embeddings-inference
Instructions to use CIRCL/vulnerability-severity-classification-roberta-base 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 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")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CIRCL/vulnerability-severity-classification-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("CIRCL/vulnerability-severity-classification-roberta-base") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -9,6 +9,8 @@ metrics:
|
|
| 9 |
model-index:
|
| 10 |
- name: vulnerability-severity-classification-roberta-base
|
| 11 |
results: []
|
|
|
|
|
|
|
| 12 |
---
|
| 13 |
|
| 14 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
@@ -86,4 +88,4 @@ The following hyperparameters were used during training:
|
|
| 86 |
- Transformers 4.51.3
|
| 87 |
- Pytorch 2.7.0+cu126
|
| 88 |
- Datasets 3.6.0
|
| 89 |
-
- Tokenizers 0.21.1
|
|
|
|
| 9 |
model-index:
|
| 10 |
- name: vulnerability-severity-classification-roberta-base
|
| 11 |
results: []
|
| 12 |
+
datasets:
|
| 13 |
+
- CIRCL/vulnerability-scores
|
| 14 |
---
|
| 15 |
|
| 16 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
|
|
| 88 |
- Transformers 4.51.3
|
| 89 |
- Pytorch 2.7.0+cu126
|
| 90 |
- Datasets 3.6.0
|
| 91 |
+
- Tokenizers 0.21.1
|