Text Classification
Transformers
Safetensors
Chinese
bert
vulnerability
severity
cybersecurity
cnvd
text-embeddings-inference
Instructions to use CIRCL/vulnerability-severity-classification-chinese-macbert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CIRCL/vulnerability-severity-classification-chinese-macbert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CIRCL/vulnerability-severity-classification-chinese-macbert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CIRCL/vulnerability-severity-classification-chinese-macbert-base") model = AutoModelForSequenceClassification.from_pretrained("CIRCL/vulnerability-severity-classification-chinese-macbert-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27be977572823a7765dea7f143872bdd83cd8ed548bd01485c185688ec168e96
- Size of remote file:
- 5.27 kB
- SHA256:
- c5afa1bfecd62ee240e124f5bb925d427a7a7373086dec2cc4205139c79849b2
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