Update app.py

app.py

@@ -2,6 +2,33 @@ import gradio as gr
 from transformers import pipeline
 p = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h")
 
+
+
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
+import torch
+
+# this model was loaded from https://hf.co/models
+model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-600M")
+tokenizer = AutoTokenizer.from_pretrained("facebook/nllb-200-distilled-600M")
+device = 0 if torch.cuda.is_available() else -1
+LANGS = ["ace_Arab", "eng_Latn", "fra_Latn", "spa_Latn", "yue_Hant","zho_Hans","zho_Hant"]
+LANGS_source = ["eng_Latn"]
+
+# Yue Chinese - yue_Hant, Chinese (Simplified)-Zho_Hans, Chinese(Traditional)-zho_Hant
+# https://github.com/facebookresearch/flores/tree/main/flores200#languages-in-flores-200
+
+def translate(text, src_lang, tgt_lang):
+    """
+    Translate the text from source lang to target lang
+    """
+    translation_pipeline = pipeline("translation", model=model, tokenizer=tokenizer, src_lang=src_lang, tgt_lang=tgt_lang, max_length=400, device=device)
+    result = translation_pipeline(text)
+    return result[0]['translation_text']
+
+
+
+
 def transcribe(audio):
     text = p(audio)["text"]
     return text