readme: ---
  language:
  - ur
  - en
  license: apache-2.0
  datasets:
  - iwslt14
  metrics:
  - bleu
  library_name: fairseq
  pipeline_tag: translation
  ---
  
  ### Urdu to English Translation
  Urdu to English translation model is a Transformer model trained on IWSLT back-translated data using Faireq. 
  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.
  The evaluation is done on WMT2017 standard test set. 
  
  * source group: English 
  * target group: Urdu 
  
  * model: transformer
  * Contextual 
  * Test Set: WMT2017
  * pre-processing: Moses + Indic Tokenizer
  * Dataset + Libray Details:  [DLNMT](https://github.com/sami-haq99/nrpu-dlnmt)
  
  ## Benchmarks
  
  | testset               | BLEU  |
  |-----------------------|-------|
  | Wmt2017  	| 50.03 	|
  
  ## How to use model?
  * This model can be accessed via git clone:
    ```
    git clone https://huggingface.co/samiulhaq/iwslt-bt-en-ur
    ```
  * You can use Fairseq library to access the model for translations:
    ```
    from fairseq.models.transformer import TransformerModel
    ```
  
  ### Load the model
  ```
  model = TransformerModel.from_pretrained('path/to/model')
  
  ```
  
  #### Set the model to evaluation mode
  ```
  model.eval()
  ```
  
  #### Perform inference
  ```
  input_text = 'Hello, how are you?'
  
  output_text = model.translate(input_text)
  
  print(output_text)
  ```
  