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--- |
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language: |
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- en |
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- ur |
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license: apache-2.0 |
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datasets: |
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- iwslt14 |
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metrics: |
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- bleu |
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library_name: fairseq |
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pipeline_tag: translation |
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--- |
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### English to Urdu Translation |
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English to Urdu translation model is a Transformer model trained on IWSLT back-translated data using Faireq. |
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This model is produced during the experimentation related to building Context-Aware NMT models for low-resourced languages such as Urdu, Hindi, Sindhi, Pashtu and Punjabi. This particular model does not contains any contextual information and it is baseline sentence-level transformer model. |
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The evaluation is done on WMT2017 standard test set. |
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* source group: English |
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* target group: Urdu |
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* model: transformer |
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* Contextual |
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* Test Set: WMT2017 |
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* pre-processing: Moses + Indic Tokenizer |
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* Dataset + Libray Details: [DLNMT](https://github.com/sami-haq99/nrpu-dlnmt) |
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## Benchmarks |
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| testset | BLEU | |
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|-----------------------|-------| |
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| Wmt2017 | 57.95 | |
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## How to use model? |
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* This model can be accessed via git clone: |
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``` |
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git clone https://huggingface.co./samiulhaq/iwslt-bt-en-ur |
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``` |
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* You can use Fairseq library to access the model for translations: |
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``` |
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from fairseq.models.transformer import TransformerModel |
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``` |
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### Load the model |
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``` |
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model = TransformerModel.from_pretrained('path/to/model') |
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``` |
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#### Set the model to evaluation mode |
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``` |
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model.eval() |
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``` |
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#### Perform inference |
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``` |
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input_text = 'Hello, how are you?' |
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output_text = model.translate(input_text) |
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print(output_text) |
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``` |
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