Usage
from sentence_transformers import SentenceTransformer, models
embedding_model = models.Transformer("yobi/klue-roberta-base-sts")
pooling_model = models.Pooling(
embedding_model.get_word_embedding_dimension(),
pooling_mode_mean_tokens=True,
)
model = SentenceTransformer(modules=[embedding_model, pooling_model])
model.encode("์๋
ํ์ธ์.", convert_to_tensor=True)
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# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("yobi/klue-roberta-base-sts") model = AutoModel.from_pretrained("yobi/klue-roberta-base-sts", device_map="auto")