Sentence Similarity
sentence-transformers
Safetensors
English
feature-extraction
dense
Generated from Trainer
dataset_size:79168
loss:LSRLoss
Instructions to use zyc-zju/qwen3-embedding-4b_search-r1_nq_lsr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use zyc-zju/qwen3-embedding-4b_search-r1_nq_lsr with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("zyc-zju/qwen3-embedding-4b_search-r1_nq_lsr") sentences = [ "other states in southeast asia that were influenced by india include", "Charles, Prince of Wales", "Cambodia", "Spanish" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| { | |
| "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", | |
| "model_type": "SentenceTransformer", | |
| "__version__": { | |
| "sentence_transformers": "5.2.0", | |
| "transformers": "4.57.2", | |
| "pytorch": "2.9.1+cu128" | |
| } | |
| } |