How to use lmtri0312/tramy-encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lmtri0312/tramy-encoder") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3]
cccda0b 048932a 96e5bf8 048932a cccda0b
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{ "word_embedding_dimension": 384, "pooling_mode_cls_token": false, "pooling_mode_mean_tokens": true, "pooling_mode_max_tokens": true, "pooling_mode_mean_sqrt_len_tokens": false }
