How to use DigitalAsocial/all-MiniLM-L6-v2-ds-rag with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DigitalAsocial/all-MiniLM-L6-v2-ds-rag") sentences = [ "Our final beliefs about θ combine both the relevant information we had a priori and the knowledge we gained a posteriori by observing data.", "To get an understanding of what the Bayesian machinery looks like in action, let us return to our coin toss example.", "In each case, the model returns a vector of size N that contains the probabilities of the N categories.", "For the moment, in fact, let us consider draws and losses to be equally bad for us." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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