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 metrics.json from peter2000/setfit-vulnerability-groups: direct link, hf CLI and curl.
- Browser
- Download file 842 Bytes
-
https://huggingface.co/peter2000/setfit-vulnerability-groups/resolve/main/metrics.json
- Command line
-
hf download hf://peter2000/setfit-vulnerability-groups/metrics.json
-
curl -L -o metrics.json https://huggingface.co/peter2000/setfit-vulnerability-groups/resolve/main/metrics.json
842 Bytes
| { | |
| "macro_f1": 0.6363926493183459, | |
| "micro_f1": 0.7068273092369478, | |
| "ece": 0.016302321274583108, | |
| "subset_accuracy": 0.5578947368421052, | |
| "per_label_f1": { | |
| "Agricultural communities": 0.8333, | |
| "Coastal communities": 0.5714, | |
| "Ethnic, racial or other minorities": 0.4444, | |
| "Fishery communities": 0.5, | |
| "Informal sector workers": 0.6667, | |
| "Members of indigenous and local communities": 0.75, | |
| "Migrants and displaced persons": 0.75, | |
| "Older persons": 0.8421, | |
| "Other": 0.4848, | |
| "Persons living in poverty": 0.6667, | |
| "Persons with disabilities": 0.875, | |
| "Persons with pre-existing health conditions": 0.5, | |
| "Residents of drought-prone regions": 0.5714, | |
| "Rural populations": 0.8, | |
| "Sexual minorities (LGBTQI+)": 0.0, | |
| "Urban populations": 0.6154, | |
| "Women and other genders": 0.9474 | |
| } | |
| } |