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")# 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 model.safetensors from CIRCL/vulnerability-severity-classification-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/CIRCL/vulnerability-severity-classification-roberta-base/resolve/main/model.safetensors
- Command line
-
hf download hf://CIRCL/vulnerability-severity-classification-roberta-base/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/CIRCL/vulnerability-severity-classification-roberta-base/resolve/main/model.safetensors
499 MB
- Xet hash:
- 7efa450f5bbca1a8d239e450cfb1735e8847f431b59f9a3a9d9751eeea645020
- Size of remote file:
- 499 MB
- SHA256:
- 7baff74e729bfec490e02777031b29182e15ca13040a3651ffe57a022cafad12
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.