Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:33684
loss:CosineSimilarityLoss
text-embeddings-inference
Instructions to use lengocquangLAB/fine-tuned-jobtitle-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lengocquangLAB/fine-tuned-jobtitle-embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lengocquangLAB/fine-tuned-jobtitle-embed") sentences = [ "Ux/Ui Designer", "Kỹ Thuật Vận Hành Voip, Tổng Đài Asterisk", "Chuyên Viên Chuyển Đổi Số (Lark-Suit)", "Nhân Viên Quản Trị Website" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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