Sentence Similarity
sentence-transformers
Safetensors
English
bert
citation-recommendation
academic
feature-extraction
text-embeddings-inference
Instructions to use galenphall/minilm-citation-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use galenphall/minilm-citation-v4 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("galenphall/minilm-citation-v4") 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:
- d6af07fcfdf2f5ad62d073c70c23a44ca966af7c99da811a07380b13b074a780
- Size of remote file:
- 90.9 MB
- SHA256:
- bd59d1745530c4fd71761acda04c211eca7e8c18366f800cea3baa403fa85849
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