How to use T-Blue/tsdae_pro_MiniLM_L12_2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("T-Blue/tsdae_pro_MiniLM_L12_2") sentences = [ "𑀟चन𑀙𑀢𑀟 𑀞च𑀪च𑀠च 𑀫𑁣प𑁣 𑀞न𑀠च 𑀞𑁣𑀱च ब𑀢𑀪𑀠च𑀯", " णच ब𑀢𑀪𑀠च पच𑀪𑁦 𑀣च 𑀠च𑀫च𑀢𑀲𑀢णच𑀪𑀳च 𑀣च झच𑀟𑁦𑀟𑀳च ञचणच𑀦 𑀞च𑀠च𑀪 णच𑀣𑀣च 𑀠च𑀫च𑀢𑀲𑀢𑀟𑀳च णच ढच𑀪 𑀢णचल𑀢𑀯", " 𑀣च𑀟बच𑀟𑁦 𑀣च 𑀟चन𑀙𑀢𑀟 𑀠𑁣पच𑀪𑀦 पच𑀟च 𑀢णच 𑀤च𑀠च ढचढढच 𑀞𑁣 𑀞च𑀪च𑀠च 𑀢𑀣च𑀟 च𑀞च 𑀞𑀱चपच𑀟पच 𑀣च 𑀠𑁣पच𑀪 𑀣चन𑀞च𑀪 𑀫𑁣प𑁣 𑀣च 𑀳नख𑀦 𑀞न𑀠च णच 𑀲𑀢 𑀟च 𑀞𑁣𑀱च ब𑀢𑀪𑀠च𑀯", "पच𑀪𑁦𑀠𑀢 णच ढनबच 𑀱च झन𑀟ब𑀢णच𑀪 झ𑀱चलल𑁣𑀟 झच𑀲च पच ञचल𑀢ढ𑀢𑀟 झच𑀳च𑀪 𑀢𑀪च𑀟 च बच𑀳च𑀪 पन𑀪𑀞𑀢णणच 𑀞न𑀠च णच त𑀢 𑀱च झन𑀟ब𑀢णच𑀪 𑀞𑀱चललचण𑁦 थ𑀯" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
