Instructions to use AutoDataBench/Retrieval-resources with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AutoDataBench/Retrieval-resources with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AutoDataBench/Retrieval-resources") 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 models/Qwen3-Embedding-0.6B/config_sentence_transformers.json from AutoDataBench/Retrieval-resources: direct link, hf CLI and curl.
- Browser
- Download file 215 Bytes
-
https://huggingface.co/AutoDataBench/Retrieval-resources/resolve/main/models/Qwen3-Embedding-0.6B/config_sentence_transformers.json
- Command line
-
hf download hf://AutoDataBench/Retrieval-resources/models/Qwen3-Embedding-0.6B/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/AutoDataBench/Retrieval-resources/resolve/main/models/Qwen3-Embedding-0.6B/config_sentence_transformers.json
215 Bytes
| { | |
| "prompts": { | |
| "query": "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery:", | |
| "document": "" | |
| }, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": "cosine" | |
| } |