Instructions to use neuralsentry/vulnfixClassification-StarEncoder-DCMB with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuralsentry/vulnfixClassification-StarEncoder-DCMB with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="neuralsentry/vulnfixClassification-StarEncoder-DCMB")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("neuralsentry/vulnfixClassification-StarEncoder-DCMB") model = AutoModelForSequenceClassification.from_pretrained("neuralsentry/vulnfixClassification-StarEncoder-DCMB") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9872d7ba2a2c86057030d635fc2e6eb86803e3b38e0f0e1c854739ba66dba65
- Size of remote file:
- 497 MB
- SHA256:
- e96925b14be3623d5bb0d47ec0f4ba6af9469ba099e4d7ae25e60f117d776623
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