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 config_setfit.json from peter2000/setfit-vulnerability-groups: direct link, hf CLI and curl.
- Browser
- Download file 610 Bytes
-
https://huggingface.co/peter2000/setfit-vulnerability-groups/resolve/main/config_setfit.json
- Command line
-
hf download hf://peter2000/setfit-vulnerability-groups/config_setfit.json
-
curl -L -o config_setfit.json https://huggingface.co/peter2000/setfit-vulnerability-groups/resolve/main/config_setfit.json
610 Bytes
| { | |
| "labels": [ | |
| "Agricultural communities", | |
| "Coastal communities", | |
| "Ethnic, racial or other minorities", | |
| "Fishery communities", | |
| "Informal sector workers", | |
| "Members of indigenous and local communities", | |
| "Migrants and displaced persons", | |
| "Older persons", | |
| "Other", | |
| "Persons living in poverty", | |
| "Persons with disabilities", | |
| "Persons with pre-existing health conditions", | |
| "Residents of drought-prone regions", | |
| "Rural populations", | |
| "Sexual minorities (LGBTQI+)", | |
| "Urban populations", | |
| "Women and other genders" | |
| ], | |
| "normalize_embeddings": false | |
| } |