Sentence Similarity
sentence-transformers
Safetensors
feature-extraction
Generated from Trainer
dataset_size:124788
loss:GISTEmbedLoss
Eval Results (legacy)
Instructions to use pj-mathematician/JobBGE-m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use pj-mathematician/JobBGE-m3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("pj-mathematician/JobBGE-m3") sentences = [ "其他机械、设备和有形货物租赁服务代表", "其他机械和设备租赁服务工作人员", "电子和电信设备及零部件物流经理", "工业主厨" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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