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
Download added_tokens.json from neuralsentry/vulnfixClassification-StarEncoder-DCMB: direct link, hf CLI and curl.
- Browser
- Download file 76 Bytes
-
https://huggingface.co/neuralsentry/vulnfixClassification-StarEncoder-DCMB/resolve/main/added_tokens.json
- Command line
-
hf download hf://neuralsentry/vulnfixClassification-StarEncoder-DCMB/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/neuralsentry/vulnfixClassification-StarEncoder-DCMB/resolve/main/added_tokens.json
76 Bytes
| { | |
| "<cls>": 49154, | |
| "<mask>": 49155, | |
| "<pad>": 49153, | |
| "<sep>": 49152 | |
| } | |