Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use peter2000/setfit-vulnerability-groups with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use peter2000/setfit-vulnerability-groups with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("peter2000/setfit-vulnerability-groups") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use peter2000/setfit-vulnerability-groups with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("peter2000/setfit-vulnerability-groups") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Download model_head.pkl from peter2000/setfit-vulnerability-groups: direct link, hf CLI and curl.
- Browser
- Download file 58.9 kB
-
https://huggingface.co/peter2000/setfit-vulnerability-groups/resolve/main/model_head.pkl
- Command line
-
hf download hf://peter2000/setfit-vulnerability-groups/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/peter2000/setfit-vulnerability-groups/resolve/main/model_head.pkl
58.9 kB
- Xet hash:
- 9c3d00e7bb0fbb103664e2f17304323496b95488556a37a9f9193d6c06bc5986
- Size of remote file:
- 58.9 kB
- SHA256:
- f3199fbbf0479014f55cf2a1816fd51512de9cf3cc83a732ac07e9d98bc1880d
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