Zen Embeddings
Collection
Embedding model family for RAG and semantic search. • 7 items • Updated
How to use zenlm/zen-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("zenlm/zen-embedding")
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]8B-parameter text-embedding model for retrieval-augmented generation, semantic search, and dense retrieval. Part of the Zen embedding line.
Repackaged from Qwen/Qwen3-Embedding-8B (apache-2.0, Alibaba Qwen). Native HuggingFace safetensors, re-hosted under the Zen embedding line. Not trained from scratch — a permissively-licensed redistribution for the OSS-clean Zen model line.
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("zenlm/zen-embedding")
emb = model.encode(["The weather is lovely today.", "It's so sunny outside!"])
print(model.similarity(emb, emb))
Hosted via the Hanzo gateway (api.hanzo.ai) as zen-embedding.
GGUF build for CPU inference: zenlm/zen-embedding-8B-GGUF.
apache-2.0. Upstream: Qwen/Qwen3-Embedding-8B by Alibaba Qwen. This repository redistributes the weights under the same license.