Instructions to use davanstrien/dataset_mentions with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use davanstrien/dataset_mentions with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("davanstrien/dataset_mentions") 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] - setfit
How to use davanstrien/dataset_mentions with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("davanstrien/dataset_mentions") - Notebooks
- Google Colab
- Kaggle
Metadata Report Card
#1
by librarian-bot - opened
Model metadata report card
This is an automatically produced metadata quality report card for davanstrien/dataset_mentions. This report is meant as a POC!
Breakdown of metadata fields for yourmodel
| Metadata Field | Provided Value |
|---|---|
| tags | Field Missing |
| license | Field Missing |
| library_name | Field Missing |
| datasets | Field Missing |
| metrics | Field Missing |
| co2 | Field Missing |
| pipeline_tag | Field Missing |
You scored a metadata coverage grade of: 0.0%
We're not angry we're just disappointed! Model metadata is super important. Please try harder...