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", device_map="auto") - Inference
- 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 | |
| 2026-07-22T10:32:32,VulnTrain,07e4bcd3-dc27-4d56-8dca-2abdf599dbec,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,17101.49111927,0.49649144895604547,2.903205606419886e-05,70.00020223721837,854.506252984916,70.0,0.3324758516935228,4.0525399956405135,0.33165999276215513,4.716675840096194,0.0,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-136-generic-x86_64-with-glibc2.39,3.12.3,3.2.9,224,Intel(R) Xeon(R) Platinum 8480+,4,4 x NVIDIA L40S,6.1327,49.6098,2015.335433959961,machine,0.9794609829135107,71.30325582760848,1.0,20.34628215353247,N,1.0,0.0 | |