Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:16729
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use hon9kon9ize/bert-large-cantonese-sts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hon9kon9ize/bert-large-cantonese-sts with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hon9kon9ize/bert-large-cantonese-sts") sentences = [ "啲狗喺雪入面玩緊。", "呢個係我成日覺得對一年級學生好有幫助嘅例子。", "兩隻狗喺沙灘到玩緊。", "喺Linux系統,我用Bibble,雖然有啲缺點,但係依家得呢個係比較專業嘅選擇。" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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