## 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:

```python
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](https://www.sbert.net/) multilingual training techniques which are available [here](https://www.sbert.net/examples/training/multilingual/README.html). 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](http://opus.nlpl.eu/) and [ParaCrawl](https://paracrawl.eu/).

{"language": "et"}
transformers pytorch distilbert feature-extraction et endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #feature-extraction #et #endpoints_compatible #region-us 

## 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:



## 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.

## 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: ## 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.
TAGS
#transformers #pytorch #distilbert #feature-extraction #et #endpoints_compatible #region-us 
 ## 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: ## 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.
passage: TAGS
#transformers #pytorch #distilbert #feature-extraction #et #endpoints_compatible #region-us 
## 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:## 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.