Sentence Similarity
sentence-transformers
Safetensors
English
Chinese
qwen2
mteb
retriever
text-embeddings-inference
custom_code
Instructions to use Kingsoft-LLM/QZhou-Embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Kingsoft-LLM/QZhou-Embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Kingsoft-LLM/QZhou-Embedding", trust_remote_code=True) 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.md
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README.md
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### Citation
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If you find our work worth citing, please use the following citation:
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@misc{qwen2.5,
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title = {Qwen2.5: A Party of Foundation Models},
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month = {September},
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year = {2024}
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}
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```
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Our tp is coming soon...
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### Citation
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If you find our work worth citing, please use the following citation:
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Our tp is coming soon...<br>
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**Qwen2.5-7B-Instruct:**
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```
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@misc{qwen2.5,
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title = {Qwen2.5: A Party of Foundation Models},
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month = {September},
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year = {2024}
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}
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```
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