Feature Extraction
sentence-transformers
Safetensors
English
bert
sentence-similarity
retrieval
tool-use
llm-agent
r-language
text-embeddings-inference
Instructions to use Stephen-SMJ/DARE-R-Retriever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Stephen-SMJ/DARE-R-Retriever with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Stephen-SMJ/DARE-R-Retriever") 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
Improve model card: add metadata, paper link, and project resources
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community team.
This PR improves the model card for DARE by:
- Adding
library_name: sentence-transformersto the metadata to enable better integration and automated code snippets. - Ensuring the
pipeline_tagis set tofeature-extraction. - Adding links to the original paper (2603.04743), the GitHub repository, and the project page.
- Including the official BibTeX citation for researchers.
- Standardizing the usage examples for better readability.
These changes help make the model more discoverable and easier for the community to use and cite.
Stephen-SMJ changed pull request status to merged