Instructions to use neuralsentry/vulnerabilityDetection-StarEncoder-Devign with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuralsentry/vulnerabilityDetection-StarEncoder-Devign with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="neuralsentry/vulnerabilityDetection-StarEncoder-Devign")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("neuralsentry/vulnerabilityDetection-StarEncoder-Devign") model = AutoModelForSequenceClassification.from_pretrained("neuralsentry/vulnerabilityDetection-StarEncoder-Devign", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from neuralsentry/vulnerabilityDetection-StarEncoder-Devign: direct link, hf CLI and curl.
- Browser
- Download file 497 MB
-
https://huggingface.co/neuralsentry/vulnerabilityDetection-StarEncoder-Devign/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://neuralsentry/vulnerabilityDetection-StarEncoder-Devign@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/neuralsentry/vulnerabilityDetection-StarEncoder-Devign/resolve/refs%2Fpr%2F1/pytorch_model.bin
497 MB
- Xet hash:
- ad2e90d918949d68a5e9139f4fae70010e4e33cc30d7a4f9f2aadeed9d715abb
- Size of remote file:
- 497 MB
- SHA256:
- 589db65adf81554c4c8aea71f0f55bfb9ee0eb4bf3d62cfb12d474f4ea2a5e32
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