Create app.py

app.py

@@ -0,0 +1,81 @@
+import os
+os.system("pip install gradio==2.8.0b2")
+import gradio as gr
+import numpy as np
+
+title = "fairseq S2S"
+
+description = "Gradio Demo for fairseq S2S: speech-to-speech translation models. To use it, simply add your audio, or click one of the examples to load them. Read more at the links below."
+
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2010.05171' target='_blank'>fairseq S2T: Fast Speech-to-Text Modeling with fairseq</a> | <a href='https://github.com/pytorch/fairseq/tree/main/examples/speech_to_text' target='_blank'>Github Repo</a></p>"
+
+examples = [
+  ["common_voice_es_en.flac","xm_transformer_600m-es_en-multi_domain"],
+  ["common_voice_ru_18945535.flac","xm_transformer_600m-ru_en-multi_domain"],
+  ["common_voice_fr_19731305.mp3","xm_transformer_600m-fr_en-multi_domain"],
+  ["common_voice_en_ru.mp3","xm_transformer_600m-en_ru-multi_domain"],
+  ["common_voice_en_es.mp3","xm_transformer_600m-en_es-multi_domain"],
+  ["common_voice_en_ar.mp3","xm_transformer_600m-en_ar-multi_domain"],
+  ["common_voice_en_tr.mp3","xm_transformer_600m-en_tr-multi_domain"],
+  ["common_voice_en_fr.mp3","xm_transformer_600m-en_fr-multi_domain"],
+  ["common_voice_en_vi.mp3","xm_transformer_600m-en_vi-multi_domain"],
+]
+
+io1 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-es_en-multi_domain")
+
+io2 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-ru_en-multi_domain")
+
+io3 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_ru-multi_domain")
+
+io4 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_es-multi_domain")
+
+io5 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_zh-multi_domain")
+
+io6 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-fr_en-multi_domain")
+
+io7 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_ar-multi_domain")
+
+io8 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_tr-multi_domain")
+
+io9 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_fr-multi_domain")
+
+io10 = gr.Interface.load("huggingface/facebook/xm_transformer_600m-en_vi-multi_domain")
+
+
+
+
+
+    
+def inference(text,model):
+   if model == "xm_transformer_600m-es_en-multi_domain":
+        outtext = io1(text)
+   elif model == "xm_transformer_600m-ru_en-multi_domain":
+        outtext = io2(text)
+   elif model == "xm_transformer_600m-en_ru-multi_domain":
+        outtext = io3(text)
+   elif model == "xm_transformer_600m-en_es-multi_domain":
+        outtext = io4(text)
+   elif model == "xm_transformer_600m-en_zh-multi_domain":
+        outtext = io5(text)
+   elif model == "xm_transformer_600m-fr_en-multi_domain":
+        outtext = io6(text)
+   elif model == "xm_transformer_600m-en_ar-multi_domain":
+        outtext = io7(text)
+   elif model == "xm_transformer_600m-en_tr-multi_domain":
+        outtext = io8(text)
+   elif model == "xm_transformer_600m-en_fr-multi_domain":
+        outtext = io9(text)
+   else:
+        outtext = io10(text)
+   return outtext 
+
+
+gr.Interface(
+    inference, 
+    [gr.inputs.Audio(label="Input",type="filepath"),gr.inputs.Dropdown(choices=["xm_transformer_600m-es_en-multi_domain","xm_transformer_600m-ru_en-multi_domain","xm_transformer_600m-en_ru-multi_domain","xm_transformer_600m-en_es-multi_domain","xm_transformer_600m-fr_en-multi_domain","xm_transformer_600m-en_ar-multi_domain","xm_transformer_600m-en_tr-multi_domain","xm_transformer_600m-en_fr-multi_domain","xm_transformer_600m-en_vi-multi_domain"], type="value", default="xm_transformer_600m-es_en-multi_domain", label="model")
+],
+    gr.outputs.Audio(label="Output"),
+    article=article,
+    title=title,
+    examples=examples,
+    description=description).launch(enable_queue=True,cache_examples=False)