sentence-transformers How to use DigitalAsocial/all-mpnet-base-v2-ds-rag-17s with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("DigitalAsocial/all-mpnet-base-v2-ds-rag-17s")
sentences = [
"Is this an invertible time series? c. What is the mean of the time series?",
"Is this a stationary time series process?",
"We can consider each conditional p(x i |pa i ) to be a factor φ i (x i , pa i ) so that we obtain the Gibbs distribution p(x) = i φ i (x i |pa i ).",
"The difference is that in the case of momentum previous weight changes are remembered, whereas here previous gradient vectors are remembered."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
