sentence-transformers How to use Jrinky/model1 with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Jrinky/model1")
sentences = [
"What surprised the author about the appearance of sloths when looking for animals to draw for the letter S",
"Third National Bank may refer to:\n\nin the United States\n(by state)\nThird National Bank (Atlanta, Georgia), now The Metropolitan (Atlanta condominium building)\n Third National Bank (Glasgow, Kentucky), listed on the NRHP in Kentucky\n Third National Bank (Ohio), a predecessor of Fifth Third Bank\n Third National Bank (Syracuse, New York), listed on the NRHP in New York\n Third National Bank (Sandusky, Ohio), listed on the NRHP in Ohio\n Third National Bank in Nashville, now incorporated within SunTrust Bank",
"S is for Sloth\nI never really paid much attention to sloths until I began searching for animals to draw for the letter S. Looking at some photos, I was shocked to see just how much they look like Muppets in real life! They're hilarious!",
"History\nThe Annual Review of Animal Biosciences was first published in 2013, with Harris A. Lewin and R. Michael Roberts as the founding co-editors. Though it was initially published in print, as of 2021 it is only published electronically. Scope and indexing\nThe Annual Review of Animal Biosciences defines its scope as covering significant developments relevant to biotechnology, genomics, genetics, veterinary medicine, animal breeding, and conservation biology. The intended audience for the journal is scientists and veterinarians involved with wild and domestic animals. It is abstracted and indexed in Scopus, Science Citation Index Expanded, MEDLINE, and Embase, among others."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
