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  ---
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  language:
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  - en
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- - gl
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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-gl trained with OPUS and HPLT data. 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: Galician
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- * Dataset: OPUS and HPLT data
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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-gl/raw/v2)
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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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-
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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 | 32.5 | 57.5 | 0.842 |
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- | ntrex | 32.7 | 56.8 | 0.7962 |
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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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