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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## Full Model Architecture
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(0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: BertModel
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(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_mean_tokens': True})
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## Full Model Architecture
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```
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CoSENT(
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(0): Transformer({'max_seq_length': 128, 'do_lower_case': False}) with Transformer model: BertModel
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(1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_mean_tokens': True})
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