Feature Extraction
sentence-transformers
ONNX
English
bert
jobs
embeddings
information-retrieval
text-embeddings-inference
Instructions to use upply-org/bge-small-jobs-data-embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use upply-org/bge-small-jobs-data-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("upply-org/bge-small-jobs-data-embedding") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b71d6462e199f72596ff16cb50a295b8719bbb038d494080026e75e120944274
- Size of remote file:
- 33.8 MB
- SHA256:
- 3f1ca2ff91c049e0b860232d38080f80851942b70ab09b875a2cb64427c844ef
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