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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d79b780b52e3ce1be6ac9db24f5c3b0630d51bbe4848d74d5e9ce8aa280fe764
- Size of remote file:
- 497 MB
- SHA256:
- 09b7ffadb9ae22c2958fc5151cf0cafd721ba5047b579b962ba9386e70a0ac0d
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