Add application file

app.py

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+import gradio as gr
+import torch
+
+from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
+
+model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_1.2B")
+tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_1.2B")
+
+langs = """Afrikaans (af), Amharic (am), Arabic (ar), Asturian (ast), Azerbaijani (az), Bashkir (ba), Belarusian (be), Bulgarian (bg), Bengali (bn), Breton (br), Bosnian (bs), Catalan; Valencian (ca), Cebuano (ceb), Czech (cs), Welsh (cy), Danish (da), German (de), Greeek (el), English (en), Spanish (es), Estonian (et), Persian (fa), Fulah (ff), Finnish (fi), French (fr), Western Frisian (fy), Irish (ga), Gaelic; Scottish Gaelic (gd), Galician (gl), Gujarati (gu), Hausa (ha), Hebrew (he), Hindi (hi), Croatian (hr), Haitian; Haitian Creole (ht), Hungarian (hu), Armenian (hy), Indonesian (id), Igbo (ig), Iloko (ilo), Icelandic (is), Italian (it), Japanese (ja), Javanese (jv), Georgian (ka), Kazakh (kk), Central Khmer (km), Kannada (kn), 
+Korean (ko), Luxembourgish; Letzeburgesch (lb), Ganda (lg), Lingala (ln), Lao (lo), Lithuanian (lt), Latvian (lv), Malagasy (mg), Macedonian (mk), Malayalam (ml), Mongolian (mn), Marathi (mr), Malay (ms), Burmese (my), Nepali (ne), Dutch; Flemish (nl), Norwegian (no), Northern Sotho (ns), Occitan (post 1500) (oc), Oriya (or), Panjabi; Punjabi (pa), Polish (pl), Pushto; Pashto (ps), Portuguese (pt), Romanian; Moldavian; Moldovan (ro), Russian (ru), Sindhi (sd), Sinhala; Sinhalese (si), Slovak (sk), 
+Slovenian (sl), Somali (so), Albanian (sq), Serbian (sr), Swati (ss), Sundanese (su), Swedish (sv), Swahili (sw), Tamil (ta), Thai (th), Tagalog (tl), Tswana (tn), 
+Turkish (tr), Ukrainian (uk), Urdu (ur), Uzbek (uz), Vietnamese (vi), Wolof (wo), Xhosa (xh), Yiddish (yi), Yoruba (yo), Chinese (zh), Zulu (zu)"""
+lang_list = [lang.strip() for lang in langs.split(',')]
+
+def translate(src, tgt, text):
+    src = src.split(" ")[-1][1:-1]
+    tgt = tgt.split(" ")[-1][1:-1]
+
+    # translate
+    tokenizer.src_lang = src
+    encoded_src = tokenizer(text, return_tensors="pt")
+    generated_tokens = model.generate(**encoded_src, forced_bos_token_id=tokenizer.get_lang_id(tgt))
+    result = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
+    return result
+
+output_text = gr.outputs.Textbox()
+gr.Interface(translate, inputs=[gr.inputs.Dropdown(lang_list, label="Source Language"), gr.inputs.Dropdown(lang_list, label="Target Language"), 'text'], outputs=output_text, title="M2M100",
+             description="100개국어 번역").launch()