Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
Instructions to use HelixAI/embed_bge_base_edu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use HelixAI/embed_bge_base_edu with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("HelixAI/embed_bge_base_edu") 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:
- 4d212f91018ef60df5de190b2531a29d6fd37f5bab1a1098b32c62b8a249da8d
- Size of remote file:
- 438 MB
- SHA256:
- 212d794f98990a0d967b9b5041739bff3ddea11882c2a75e64252309e7cc2793
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