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:
- f55ce7e67a2f6aeb9b2c36aa883a7a235edb99c560839c0bd6dbe659f86f811f
- Size of remote file:
- 4.09 kB
- SHA256:
- dff907b94e249c5ad678b0618d20368547f6373cc26e2c133882bd32521a7b1b
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