How to use swardiantara/bert-tiny-snli-k1-fixed-cosine with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("swardiantara/bert-tiny-snli-k1-fixed-cosine") sentences = [ "Young blond woman putting her foot into a water fountain [SEP] A young blond woman is sitting down on a beach chair.", "A young boy is posing for a picture at the beach next to a yellow watering can on a stick and a red folding chair. [SEP] The boy loves the beach.", "A young shirtless boy in kakhi pants is kneeling in a marsh while someone splashes nearby. [SEP] Two people are riding on a ferris wheel at the fair.", "A girl in a white shirt is sitting on a park bench with a dog next to her. [SEP] The girl and the dog are outdoors." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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