Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
Instructions to use huiwonLee/LABSE_ft_employee_sts_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use huiwonLee/LABSE_ft_employee_sts_v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("huiwonLee/LABSE_ft_employee_sts_v1") 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
- Xet hash:
- ba27606b66c29a1e16647292f57c0cfba58c8b53eed6e7415eaf9f2d300836d9
- Size of remote file:
- 1.88 GB
- SHA256:
- af87e2198a70f4eeae872deb557bbac3949fbb3dae7a5dbba0868fa1f9ff7287
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