update model and gr
Browse files
README.md
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## Info
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Using facebook/
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facebook/
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Here, this app uses/tests these languages only.
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## Read more:
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https://huggingface.co/facebook/
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## Info
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Using facebook/m2m100-12B-avg-5-ckpt pre-trained model
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facebook/m2m100-12B-avg-5-ckpt supports 100 languages.
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Here, this app uses/tests these languages only.
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## Read more:
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https://huggingface.co/facebook/m2m100-12B-avg-5-ckpt
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app.py
CHANGED
@@ -10,7 +10,7 @@ tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_1.2B")
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this_description = '''
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Using facebook/
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Chinese(zh)
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English(en)
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Hindi(hi)
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Sinhalese(si)
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Thai(th)
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Vietnamese(vi)
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'''
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def m2m_translate(Input_Text, from_lang, to_lang):
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tokenizer.src_lang = from_lang
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encoded_from_lang = tokenizer(Input_Text, return_tensors="pt")
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generated_tokens = model.generate(
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**encoded_from_lang, forced_bos_token_id=tokenizer.get_lang_id(to_lang))
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res = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
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@@ -39,35 +144,41 @@ def m2m_translate(Input_Text, from_lang, to_lang):
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iface = gr.Interface(
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fn=m2m_translate,
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title="M2M100 Translation",
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description=this_description,
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inputs=[
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gr.
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gr.
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],
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outputs="text")
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this_description = '''
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Using facebook/m2m100-12B-avg-5-ckpt pre-trained model. Language code:
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Chinese(zh)
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English(en)
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Hindi(hi)
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Sinhalese(si)
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Thai(th)
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Vietnamese(vi)
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...
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'''
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# From facebook/m2m100-12B-avg-5-ckpt
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lang_codes = {
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"Afrikaans": "af",
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"Amharic": "am",
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"Arabic": "ar",
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"Asturian": "ast",
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"Azerbaijani": "az",
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"Bashkir": "ba",
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"Belarusian": "be",
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"Bulgarian": "bg",
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"Bengali": "bn",
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"Breton": "br",
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"Bosnian": "bs",
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"Catalan; Valencian": "ca",
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"Cebuano": "ceb",
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"Czech": "cs",
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"Welsh": "cy",
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"Danish": "da",
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"German": "de",
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"Greeek": "el",
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"English": "en",
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"Spanish": "es",
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"Estonian": "et",
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"Persian": "fa",
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"Fulah": "ff",
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"Finnish": "fi",
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"French": "fr",
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"Western Frisian": "fy",
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"Irish": "ga",
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"Gaelic; Scottish Gaelic": "gd",
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"Galician": "gl",
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"Gujarati": "gu",
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"Hausa": "ha",
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"Hebrew": "he",
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"Hindi": "hi",
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"Croatian": "hr",
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"Haitian; Haitian Creole": "ht",
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"Hungarian": "hu",
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"Armenian": "hy",
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"Indonesian": "id",
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"Igbo": "ig",
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"Iloko": "ilo",
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"Icelandic": "is",
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"Italian": "it",
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"Japanese": "ja",
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"Javanese": "jv",
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"Georgian": "ka",
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"Kazakh": "kk",
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"Central Khmer": "km",
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"Kannada": "kn",
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"Korean": "ko",
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"Luxembourgish; Letzeburgesch": "lb",
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"Ganda": "lg",
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"Lingala": "ln",
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"Lao": "lo",
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"Lithuanian": "lt",
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"Latvian": "lv",
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"Malagasy": "mg",
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"Macedonian": "mk",
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"Malayalam": "ml",
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"Mongolian": "mn",
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"Marathi": "mr",
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"Malay": "ms",
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"Burmese": "my",
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"Nepali": "ne",
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"Dutch; Flemish": "nl",
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"Norwegian": "no",
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"Northern Sotho": "ns",
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"Occitan": "oc",
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"Oriya": "or",
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"Panjabi; Punjabi": "pa",
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"Polish": "pl",
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"Pushto": "ps",
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"Portuguese": "pt",
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"Romanian; Moldavian; Moldovan": "ro",
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"Russian": "ru",
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"Sindhi": "sd",
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"Sinhala; Sinhalese": "si",
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"Slovak": "sk",
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"Slovenian": "sl",
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"Somali": "so",
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"Albanian": "sq",
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"Serbian": "sr",
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"Swati": "ss",
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"Sundanese": "su",
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"Swedish": "sv",
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"Swahili": "sw",
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"Tamil": "ta",
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"Thai": "th",
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"Tagalog": "tl",
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"Tswana": "tn",
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"Turkish": "tr",
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"Ukrainian": "uk",
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"Urdu": "ur",
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"Uzbek": "uz",
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"Vietnamese": "vi",
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"Wolof": "wo",
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"Xhosa": "xh",
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"Yiddish": "yi",
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"Yoruba": "yo",
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"Chinese": "zh",
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"Zulu": "zu"
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}
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def m2m_translate(Input_Text, from_lang, to_lang):
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tokenizer.src_lang = lang_codes[from_lang]
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encoded_from_lang = tokenizer(Input_Text, return_tensors="pt")
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generated_tokens = model.generate(
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**encoded_from_lang, forced_bos_token_id=tokenizer.get_lang_id(lang_codes[to_lang]))
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res = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
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iface = gr.Interface(
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fn=m2m_translate,
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title="M2M100 Text Translation",
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description=this_description,
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inputs=[
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gr.Textbox(lines=5, placeholder="Enter text", label="Text input"),
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gr.Radio(
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choices=[
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'Burmese',
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'Chinese',
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'English',
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'Hindi',
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'Japanese',
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'Sinhala',
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'Thai',
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'Vietnamese'
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],
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default='Vietnamese',
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label='From language'
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),
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gr.Radio(
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choices=[
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'Burmese',
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'Chinese',
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'English',
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'Hindi',
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'Japanese',
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'Sinhala',
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'Thai',
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'Vietnamese'
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],
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default='English',
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label='To language'
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),
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],
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outputs="text")
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