metadata
language:
- en
- ur
license: apache-2.0
datasets:
- iwslt14
metrics:
- bleu
library_name: fairseq
pipeline_tag: translation
English to Urdu Translation
English to Urdu 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
Benchmarks
| testset | BLEU |
|---|---|
| Wmt2017 | 57.95 |
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)