sentence-transformers How to use Tien09/tiny_bert_ft_sim_score_1 with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("Tien09/tiny_bert_ft_sim_score_1")
sentences = [
"This card is treated as a Normal Monster while face-up on the field or in the GY. While this card is face-up on the field, you can Normal Summon it to have it become an Effect Monster with this effect. During your End Phase: You can target 1 Equip Spell Card in your GY; add that target to your hand. You can only use this effect of \"Knight Day Grepher\" once per turn.",
"2 Beast-Warrior monsters, including a WIND \"Ancient Warriors\" monster\r\nAll \"Ancient Warriors\" monsters you control gain 500 ATK/DEF. You can only use each of the following effects of \"Ancient Warriors Oath - Double Dragon Lords\" once per turn. If this card is Link Summoned: You can add 1 \"Ancient Warriors\" card from your Deck to your hand. (Quick Effect): You can send 1 card from your hand or field to the GY, then target 1 face-up card your opponent controls; return it to the hand.",
"Place 1 Ocean Counter on this card during each player's Standby Phases. When this card is removed from the field, all Fish-Type and Sea Serpent-Type monsters you control gain 200 ATK for each Ocean Counter on this card, until the End Phase.",
"If you have no cards in your GY (Quick Effect): You can send this card from your hand to the GY; until the end of the next turn, any card sent to the GY is banished instead."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
