Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
Chinese
bert
Sentence Transformers
Instructions to use shibing624/text2vec-base-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use shibing624/text2vec-base-chinese with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("shibing624/text2vec-base-chinese") sentences = [ "那是 個快樂的人", "那是 條快樂的狗", "那是 個非常幸福的人", "今天是晴天" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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- feature-extraction
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- sentence-similarity
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- transformers
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---
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# shibing624/text2vec-base-chinese
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This is a CoSENT(Cosine Sentence) model: shibing624/text2vec-base-chinese.
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year = {2022},
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url = {https://github.com/shibing624/text2vec},
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}
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```
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- feature-extraction
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- sentence-similarity
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- transformers
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datasets:
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- shibing624/nli_zh
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language:
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- zh
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metrics:
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- bleu
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library_name: transformers
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---
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# shibing624/text2vec-base-chinese
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This is a CoSENT(Cosine Sentence) model: shibing624/text2vec-base-chinese.
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year = {2022},
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url = {https://github.com/shibing624/text2vec},
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}
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```
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