How to use deepapaikar/gte-small-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("deepapaikar/gte-small-finetuned") sentences = [ "whine stare jelli comfort fairmount former poni guttur innoc latitud ceas firm spoil impress base sentiment aeroplan globe usurp monogram keen frau opposit reimburs express ever craze oil bade directric save notic helmet proper schmierkäs pale engrav chateau pair sleep cautious audibl squar disinclin keeper gosh ravag brigandish stammer death colleg suit treason year storekeep rib wake gaunt appear perforc afterward intim noisi goodi fear illumin marvel mantel volum health belief soften conclus rode social sip tip mina wing suppli tommi slight pomatum bombard simpli foreign mustard leg semi twist bend helen flush rough wound rifl unqualifi shill soon enorm gloomi depress scratch soil car broken slam count grace millineri pour swirl depriv smell strode direct wholli method modest shift immigr finger leon differ worker fetch advis hord affair ardmor rivet white four occup burst ridg exclam knuckl interest dead dentist wreckag drizzl kraus famous chariti vite permiss jabez written twice pile loyalti frenchman shine wave meat rang civilian deserv forev slip halt see charact feed foremost uniform chime within suspect mount bash often lath outlin aim straw distract past erupt seren whoever whenev fall doughboy remain scoot lawn task spectat altar bavarian spirit either sold individu hillsid easili wick dream brain guess floor start decor incid dramat condit guest accus monteith rumbl camp wherev truer blanket brown puzzl distanc sight addit head withdrew everybodi ahead morn sought lost besid fli snatch local mutil contribut pat cover behalf contest whistl futur hope patriot weari law area brancardi block nose push girl conceiv offer fisherman stroll appeal bail stone suppos caught amaz subsid bundl tack poorest roadsid princ miss clamor held retir felt signific annex 1918 wild come whether demur mutter hesit panopli hetti soundless felin patri bombast dyke concoct busili result impati covert stall mademoisell danger moon grave abrupt dim goggl light overturn brought imaginari statement commiss unbroken found", "Is the content related to fiction genere", "Is the content related to non-fiction genere", "Is the content related to fiction genere" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
