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
Download tokenizer.json from Stephen-SMJ/DARE-R-Retriever: direct link, hf CLI and curl.
- Browser
- Download file 712 kB
-
https://huggingface.co/Stephen-SMJ/DARE-R-Retriever/resolve/main/tokenizer.json
- Command line
-
hf download hf://Stephen-SMJ/DARE-R-Retriever/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Stephen-SMJ/DARE-R-Retriever/resolve/main/tokenizer.json
712 kB
File too large to display, you can check the raw version instead.