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
File size: 282 Bytes
35d8f09 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"__version__": {
"sentence_transformers": "5.2.2",
"transformers": "5.0.0",
"pytorch": "2.9.0+cu126"
},
"model_type": "SentenceTransformer",
"prompts": {
"query": "",
"document": ""
},
"default_prompt_name": null,
"similarity_fn_name": "cosine"
} |