Sentence Similarity
sentence-transformers
Safetensors
roberta
feature-extraction
Generated from Trainer
dataset_size:6000
loss:CosineSimilarityLoss
Eval Results (legacy)
Instructions to use Kao1412/Classification_Address_New with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Kao1412/Classification_Address_New with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Kao1412/Classification_Address_New") sentences = [ "64 /161 c số92 phường linh trung quận quận tân bình long an", "179 /108 a số53 đường nguyễn văn cừ phường quận thanh xuân hà nội", "184 /22 c số116 ngõ196 điện biên phủ quận đống đa hải phòng", "64 /161 c số92 phường linh trung quận quận tân bình long an" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| } | |
| ] |