Text Classification
Transformers
PyTorch
Safetensors
roberta
Generated from Trainer
classification
nlp
vulnerability
CWE
text-embeddings-inference
Instructions to use CIRCL/cwe-parent-vulnerability-classification-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIRCL/cwe-parent-vulnerability-classification-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CIRCL/cwe-parent-vulnerability-classification-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CIRCL/cwe-parent-vulnerability-classification-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("CIRCL/cwe-parent-vulnerability-classification-roberta-base") - Notebooks
- Google Colab
- Kaggle
| timestamp,project_name,run_id,experiment_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,water_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,cpu_utilization_percent,gpu_utilization_percent,ram_utilization_percent,ram_used_gb,on_cloud,pue,wue | |
| 2026-01-13T21:56:14,codecarbon,393db334-33a7-40a5-8744-5c0c0b8e9695,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,1567.7256346759968,0.06313669868117386,4.02727985590555e-05,368.66620928434594,938.1824499334339,70.0,0.1616492382015093,0.407745279251518,0.030405019717430055,0.5997995371704574,0.0,Luxembourg,LUX,,,,Linux-6.8.0-90-generic-x86_64-with-glibc2.39,3.12.3,3.2.1,224,Intel(R) Xeon(R) Platinum 8480+,4,4 x NVIDIA L40S,6.1661,49.7498,2015.3354835510254,machine,0.6375481386392811,72.2033055198973,4.556418485237484,91.88500246187536,N,1.0,0.0 | |