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update README
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README.md
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---
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language:
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- en
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tags:
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- translation
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license: cc-by-4.0
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---
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This repository contains the translation model for en-
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### Model Info
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* Source language: English
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* Target language:
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*
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* Model architecture: Transformer-base
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* Tokenizer: SentencePiece (Unigram)
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* Cleaning: We used OpusCleaner with a set of basic rules. Details can be found in the filter files in [Github](https://github.com/hplt-project/HPLT-MT-Models/tree/main/v1.0/data/en-
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You can also read our deliverable report [here](https://hplt-project.org/HPLT_D5_1___Translation_models_for_select_language_pairs.pdf) for more details.
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### Usage
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The model has been trained with Marian. To run inference, refer to the [Inference/Decoding/Translation](https://github.com/hplt-project/HPLT-MT-Models/tree/main/v1.0#inferencedecodingtranslation) section of our GitHub repository.
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The model can be used with the Hugging Face framework if the weights are converted to the Hugging Face format. We might provide this in the future; contributions are also welcome.
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| testset | BLEU | chrF++ | COMET22 |
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| -------------------------------------- | ---- | ----- | ----- |
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| flores200 |
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| ntrex |
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### Acknowledgements
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---
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language:
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- en
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- hr
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tags:
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- translation
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license: cc-by-4.0
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---
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### HPLT MT release v1.0
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This repository contains the translation model for en-hr trained with HPLT data only. For usage instructions, evaluation scripts, and inference scripts, please refer to the [HPLT-MT-Models v1.0](https://github.com/hplt-project/HPLT-MT-Models/tree/main/v1.0) GitHub repository.
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### Model Info
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* Source language: English
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* Target language: Croatian
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* Data: HPLT data only
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* Model architecture: Transformer-base
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* Tokenizer: SentencePiece (Unigram)
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* Cleaning: We used OpusCleaner with a set of basic rules. Details can be found in the filter files in [Github](https://github.com/hplt-project/HPLT-MT-Models/tree/main/v1.0/data/en-hr/raw/v0)
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You can also read our deliverable report [here](https://hplt-project.org/HPLT_D5_1___Translation_models_for_select_language_pairs.pdf) for more details.
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### Usage
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**Note** that for quality considerations, we recommend using [HPLT/translate-en-hr-v1.0-hplt_opus](https://huggingface.co/HPLT/translate-en-hr-v1.0-hplt_opus) instead of this model.
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The model has been trained with Marian. To run inference, refer to the [Inference/Decoding/Translation](https://github.com/hplt-project/HPLT-MT-Models/tree/main/v1.0#inferencedecodingtranslation) section of our GitHub repository.
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The model can be used with the Hugging Face framework if the weights are converted to the Hugging Face format. We might provide this in the future; contributions are also welcome.
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## Benchmarks
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| testset | BLEU | chrF++ | COMET22 |
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| -------------------------------------- | ---- | ----- | ----- |
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| flores200 | 28.4 | 54.9 | 0.8664 |
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| ntrex | 28.3 | 53.9 | 0.8092 |
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### Acknowledgements
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