Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:6500
loss:CosineSimilarityLoss
Eval Results (legacy)
Instructions to use Kao1412/Classification_Address with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Kao1412/Classification_Address with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Kao1412/Classification_Address") sentences = [ "64 đường tố hữu đông anh hải phòng", "64 đường tố hữu đông anh hải phòng", "80 mễ trì phú nhuận tp cà mau", "81 phùng khồang phường quận 6 đà nẵng" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 294665039a21bf79f991732df4ca86756ce65ff4d82226a4eab21dc375a27357
- Size of remote file:
- 540 MB
- SHA256:
- 9a002b3bdab6acb95f9e88a9c72e91e584d079cf538d3b246fc2dd920368acdc
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