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update README

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  ---
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  language:
 
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  - en
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- - bs
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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-bs 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: Bosnian
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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/bs-en/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-bs-v1.0-hplt_opus](https://huggingface.co/HPLT/translate-en-bs-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 | 4.7 | 26.0 | 0.4314 |
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- | ntrex | 4.1 | 23.9 | 0.4178 |
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  ### Acknowledgements
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  ---
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  language:
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+ - ar
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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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+ ## HPLT MT release v1.0
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+ This repository contains the translation model for ar-en 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: Arabic
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+ * Target language: English
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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/ar-en/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 | 40.1 | 63.1 | 0.8645 |
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+ | ntrex | 34.7 | 58.9 | 0.8426 |
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  ### Acknowledgements
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