Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
classification
nlp
vulnerability
Eval Results (legacy)
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")# pip install -U transformers accelerate # 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
Download emissions.csv from CIRCL/vulnerability-severity-classification-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 831 Bytes
-
https://huggingface.co/CIRCL/vulnerability-severity-classification-roberta-base/resolve/e767b765341c478fac645a14c6d4b2eb61328ec6/emissions.csv
- Command line
-
hf download hf://CIRCL/vulnerability-severity-classification-roberta-base@e767b765341c478fac645a14c6d4b2eb61328ec6/emissions.csv
-
curl -L -o emissions.csv https://huggingface.co/CIRCL/vulnerability-severity-classification-roberta-base/resolve/e767b765341c478fac645a14c6d4b2eb61328ec6/emissions.csv
831 Bytes
| 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,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,on_cloud,pue | |
| 2025-03-11T13:42:52,codecarbon,10e7964a-d760-482a-a624-97b76663bf5d,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,22333.945179948583,0.3920252870180382,1.755289017947436e-05,42.5,182.39382883775872,94.34470081329346,0.26345167142701137,2.8759955588501214,0.5847985827629493,3.7242458130400817,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-48-generic-x86_64-with-glibc2.39,3.12.3,2.8.3,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.58586883544922,machine,N,1.0 | |