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")# pip install -U transformers accelerate # 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
Download pytorch_model.bin from neuralsentry/vulnfixClassification-StarEncoder-DCMB: direct link, hf CLI and curl.
- Browser
- Download file 497 MB
-
https://huggingface.co/neuralsentry/vulnfixClassification-StarEncoder-DCMB/resolve/370c22eabbcd108ccb3e940e45f68a640c8c8491/pytorch_model.bin
- Command line
-
hf download hf://neuralsentry/vulnfixClassification-StarEncoder-DCMB@370c22eabbcd108ccb3e940e45f68a640c8c8491/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/neuralsentry/vulnfixClassification-StarEncoder-DCMB/resolve/370c22eabbcd108ccb3e940e45f68a640c8c8491/pytorch_model.bin
497 MB
- Xet hash:
- ae85974999714c5782602368fee024667e6d14b63e0f2a6ef72f311e6a67befe
- Size of remote file:
- 497 MB
- SHA256:
- 6888b0fe587a6ed3975a6a1c06ad29792e8a0f46aded8702ed88904177ea1195
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