sentence-transformers How to use Stffens/bge-small-rrf-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Stffens/bge-small-rrf-v1")
sentences = [
"blood clots",
"Herbal infusions as a source of calcium, magnesium, iron, zinc and copper in human nutrition.\nThe study material consisted of five herbs: chamomile (flowers), mint (leaves), St John's wort (flowers and leaves), sage (leaves) and nettle (leaves), sourced from three producers. The calcium, magnesium, iron, zinc and copper contents were determined for both dried herb samples and prepared infusions, and the extraction rates were calculated. Mineral components were determined using atomic absorption spectrometry",
"Vegetarian diets and incidence of diabetes in the Adventist Health Study-2\nAim To evaluate the relationship of diet to incident diabetes among non-Black and Black participants in the Adventist Health Study-2. Methods and Results Participants were 15,200 men and 26,187 women (17.3% Blacks) across the U.S. and Canada who were free of diabetes and who provided demographic, anthropometric, lifestyle and dietary data. Participants were grouped as vegan, lacto ovo vegetarian, pesco vegetarian, semi-vegetarian or ",
"Green tea: nature's defense against malignancies.\nThe current practice of introducing phytochemicals to support the immune system or fight against diseases is based on centuries old traditions. Nutritional support is a recent advancement in the domain of diet-based therapies; green tea and its constituents are one of the important components of these strategies to prevent and cure various malignancies. The anti-carcinogenic and anti-mutagenic activities of green tea were highlighted some years ago suggestin"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
