Instructions to use joshcx/static-embedding-bge-large-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use joshcx/static-embedding-bge-large-en with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("joshcx/static-embedding-bge-large-en") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bc5d3c8adbbe1ce56a2f06090c02fc958af88330cd26cce3b77c7bcd7c9ba4d2
- Size of remote file:
- 30.2 MB
- SHA256:
- d6c04b645b1611f9654e149dee254377f961fade290566bea3dd1703879629ad
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