This model is based off Sentence-Transformer's
distiluse-base-multilingual-cased multilingual model that has been extended to understand sentence embeddings in Estonian.
This model can be imported directly via the SentenceTransformers package as shown below:
from sentence_transformers import SentenceTransformer model = SentenceTransformer('kiri-ai/distiluse-base-multilingual-cased-et') sentences = ['Here is a sample sentence','Another sample sentence'] embeddings = model.encode(sentences) print("Sentence embeddings:") print(embeddings)
The fine-tuning and training processes were inspired by sbert's multilingual training techniques which are available here. The documentation shows and explains the step-by-step process of using parallel sentences to train models in a different language.
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