Sentence Similarity
sentence-transformers
Safetensors
Transformers
Chinese
roformer
feature-extraction
cmteb
custom_code
Instructions to use infly/inf-wse-v1-base-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use infly/inf-wse-v1-base-zh with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("infly/inf-wse-v1-base-zh", trust_remote_code=True) 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] - Transformers
How to use infly/inf-wse-v1-base-zh with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("infly/inf-wse-v1-base-zh", trust_remote_code=True) model = AutoModel.from_pretrained("infly/inf-wse-v1-base-zh", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7b55ef0dd2aef4c22b3986eeecf2e4420397b766d6c52b8a8a339f0339d0e2c0
- Size of remote file:
- 495 MB
- SHA256:
- 86173a3f7b0551db07283cea1a4bdf092dbeabeb6cace5c022883289265ae549
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