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distiluse-base-multilingual-cased-et
kiri-ai/distiluse-base-multilingual-cased-et
distiluse-base-multilingual-cased-et is a feature extraction model from kiri-ai. Use it when you need embeddings to search or compare text. It is set up for transformers.
This model is based off Sentence-Transformer's distiluse-base-multilingual-cased multilingual model that has been extended to understand sentence embeddings in Estonian.
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At a glance
- Task
- Feature Extraction
- Library
- transformers
- Model type
- distilbert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Dec 11, 2020
- SHA
- 4cc7064d
Model card
From the Hugging Face model README
Model Description
This model is based off Sentence-Transformer's distiluse-base-multilingual-cased multilingual model that has been extended to understand sentence embeddings in Estonian.
Sentence-Transformers
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)
Fine-tuning
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.
Resources
The model was fine-tuned on English-Estonian parallel sentences taken from OPUS and ParaCrawl.
- Task
- Feature Extraction
- Library
- transformers
- Type
- distilbert
- Languages
- et
- Created
- Mar 2, 2022
- Updated
- Dec 11, 2020