Sentence Similarity
sentence-transformers
Safetensors
bert
retrieval
recommendation
recovery-nutrition
text-embeddings-inference
Instructions to use benjac8/biobite-retriever with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use benjac8/biobite-retriever with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("benjac8/biobite-retriever") 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
| model,precision@3,precision@3_ci_low,precision@3_ci_high,mrr,ndcg@10,dim,params_M,corpus_encode_sec,query_ms | |
| TF-IDF baseline,0.6342592592592592,0.5555555555555556,0.7083333333333334,0.7500112734487734,0.579673539416922,46766,0.0,0.3930225829826668,0.2101342640041063 | |
| e5-small-v2,0.5509259259259259,0.462962962962963,0.6388888888888888,0.6768514133632961,0.5380648090238983,384,33.4,135.099265167024,3.6766076389337994 | |
| bge-small-en-v1.5,0.5416666666666666,0.45370370370370366,0.6342592592592592,0.6448808696834653,0.5087893014351133,384,33.4,121.17169079201994,3.604080444751566 | |
| all-MiniLM-L6-v2,0.37037037037037035,0.28703703703703703,0.4583333333333333,0.5155707143344456,0.3577387444600435,384,22.7,59.5438565830118,1.644114000050144 | |