Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
Generated from Trainer
dataset_size:1615
loss:TripletLoss
Eval Results (legacy)
Instructions to use tdm503/spcc-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tdm503/spcc-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tdm503/spcc-finetuned") sentences = [ "工事キャンセル日を変更したい", "工事予定キャンセルしたため日程変更手続き希望", "予定キャンセルした工事日を再調整希望", "新規工事日を早めてほしい" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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