Feature Extraction
sentence-transformers
Safetensors
English
Chinese
qwen3
zen
zen-embedding
zenlm
hanzo
embedding
retrieval
text-embeddings-inference
Instructions to use zenlm/zen-embedding-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use zenlm/zen-embedding-0.6B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("zenlm/zen-embedding-0.6B") 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
Add NOTICE: Copyright Zen Authors
Browse files
NOTICE
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
Zen
|
| 2 |
+
Copyright 2025-2026 Zen Authors
|
| 3 |
+
|
| 4 |
+
This model and its accompanying code are licensed under the Apache License, Version 2.0.
|
| 5 |
+
Zen models are developed by the Zen Authors (https://zenlm.org).
|
| 6 |
+
|
| 7 |
+
This model is derived from an upstream base model (Qwen3-Embedding-0.6B),
|
| 8 |
+
distributed under a compatible permissive license. Upstream
|
| 9 |
+
attribution is retained as required by that license.
|