Text Classification
Transformers
PyTorch
Safetensors
roberta
Generated from Trainer
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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 5
Browse files- emissions.csv +2 -1
- model.safetensors +1 -1
emissions.csv
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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
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2025-08-14T13:21:22,codecarbon,ba1ccfe9-3b30-43eb-906d-3d06569c6836,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,68.45785333399999,0.
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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
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2025-08-14T13:21:22,codecarbon,ba1ccfe9-3b30-43eb-906d-3d06569c6836,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,68.45785333399999,0.0010607051604809,1.5494280185881323e-05,42.5,390.52603588425,94.34468507766724,0.0008076901581395,0.007476145425356,0.0017928785561448,0.0100767141396403,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-71-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.5858268737793,machine,N,1.0
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2025-08-14T13:23:37,codecarbon,ba1ccfe9-3b30-43eb-906d-3d06569c6836,5b0fa12a-3dd7-45bb-9766-cc326314d9f1,203.14998063099983,0.0031044409012440074,1.528152201443175e-05,42.5,382.1036703910814,94.34468507766725,0.0023977513118243043,0.021771872417483993,0.005322609070858969,0.029492232800167266,Luxembourg,LUX,luxembourg,,,Linux-6.8.0-71-generic-x86_64-with-glibc2.39,3.12.3,2.8.4,64,AMD EPYC 9124 16-Core Processor,2,2 x NVIDIA L40S,6.1294,49.6113,251.5858268737793,machine,N,1.0
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model.safetensors
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size 499178216
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