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
Add exported onnx model 'model_O4.onnx' (#29)
Browse files- Add exported onnx model 'model_O4.onnx' (40c402eb60e4916ab32524e00763308b0d6fc882)
Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>
- onnx/model_O4.onnx +3 -0
onnx/model_O4.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:5db146ea8e6ef7d334d754beaf38d6387ddda32f59e995ae1286ef87e4f13640
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size 203394875
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