Sentence Similarity
sentence-transformers
Safetensors
English
Chinese
multilingual
qwen3
feature-extraction
embedding
text-embedding
retrieval
text-embeddings-inference
Instructions to use Octen/Octen-Embedding-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Octen/Octen-Embedding-8B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Octen/Octen-Embedding-8B") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Update README
Browse files
README.md
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@@ -114,7 +114,7 @@ If you use this model in your research, please cite:
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title={Octen-Embedding-8B: A Fine-tuned Multilingual Text Embedding Model},
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author={Octen Team},
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year={2025},
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url={https://huggingface.co/}
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}
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```
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title={Octen-Embedding-8B: A Fine-tuned Multilingual Text Embedding Model},
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author={Octen Team},
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year={2025},
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url={https://huggingface.co/bflhc/Octen-Embedding-8B}
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}
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```
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