Create app.py

app.py

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+import os
+import gradio as gr
+from simpletransformers.seq2seq import Seq2SeqModel, Seq2SeqArgs
+
+
+# os.environ["TOKENIZERS_PARALLELISM"] = "false"
+
+
+def load_translator(model_name='Enutrof/marian-mt-en-pcm'):
+    '''
+    This method loads the sequence to sequence model for translation.
+    :return: model
+    '''
+    pmodel_args = Seq2SeqArgs()
+    pmodel_args.max_length = 1024
+    pmodel_args.length_penalty = 1
+    pmodel_args.num_beams = 20
+    pmodel_args.num_return_sequences = 3
+
+    pmodel = Seq2SeqModel(
+        encoder_decoder_type="marian",
+        encoder_decoder_name=model_name,
+        args=pmodel_args,
+        use_cuda=False
+    )
+    return pmodel
+
+
+en_pcm_model = load_translator()
+
+
+def predict(input):
+    if isinstance(input, str):
+        input = [input]
+    predictions = en_pcm_model.predict(input)
+    return [i.replace('▁', ' ') for i in predictions[0]]
+
+
+# HF_TOKEN = os.getenv('english-pidgin-flagging')
+# hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN,
+#                                        dataset_name="English-NigerianPidgin-Result-Validation",
+#                                        organization="Enutrof",
+#                                        )
+gr.Interface(
+    fn=predict,
+    inputs=gr.inputs.Textbox(lines=1, label="Input Text in English"),
+    outputs=[
+        gr.outputs.Textbox(label="Translated texts in 🇳🇬 Pidgin"),
+        gr.outputs.Textbox(label=''),
+        gr.outputs.Textbox(label=''),
+    ],
+    # theme="peach",
+    title='English to 🇳🇬 Pidgin Automatic Translation',
+    description='Type your English text in the left text box to get 🇳🇬 Pidgin translations on the right. '
+                'Tell us the best translation by clicking one of the buttons below.',
+    examples=[
+        'Who are you?',
+        'You shall not pervert justice due the stranger or the fatherless, nor take a widow’s garment as a pledge.',
+        'I know every song by that artiste.',
+        'They should not be permitted here.',
+        'What are you looking for?',
+        'I am lost please help me find my way to the market.',
+    ],
+    allow_flagging="manual",
+    flagging_options=["translation 1 ✅", "translation 2 ✅",
+                      "translation 3 ✅"],
+    #flagging_callback=hf_writer,
+).launch(enable_queue=True)