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curl http://localhost:8080/embed \
-X POST \
-d '{"inputs": ["Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery: What is the capital of China?", "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery: Explain gravity"]}' \
-H "Content-Type: application/json"
is "Instruct: X \n Query: X" format important?
Can I just use freestyle instructions format like this: ?
Generate document embeddings like this:
"Represent this food blog post title for semantic search: Easy Homemade Pizza Recipe"
Generate for user searches like this:
"Encode this search query for retrieving food blog posts: quick pizza dough"
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https://huggingface.co/Qwen/Qwen3-Embedding-0.6B - this embedding model.
Questions:
Is it similar to TEI instructions? would I use the same format in llama.cpp?:
https://huggingface.co/Qwen/Qwen3-Embedding-0.6B#text-embeddings-inference-tei-usage
curl http://localhost:8080/embed \ -X POST \ -d '{"inputs": ["Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery: What is the capital of China?", "Instruct: Given a web search query, retrieve relevant passages that answer the query\nQuery: Explain gravity"]}' \ -H "Content-Type: application/json"is "Instruct: X \n Query: X" format important?
Can I just use freestyle instructions format like this: ?
Generate document embeddings like this:
Generate for user searches like this:
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