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import gradio as gr |
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import os |
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import torch |
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import gradio as gr |
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from transformers import M2M100Tokenizer, M2M100ForConditionalGeneration |
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if torch.cuda.is_available(): |
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device = torch.device("cuda:0") |
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else: |
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device = torch.device("cpu") |
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tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_1.2B") |
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model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_1.2B").to(device) |
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model.eval() |
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class Language: |
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def __init__(self, name, code): |
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self.name = name |
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self.code = code |
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lang_id = [ |
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Language("Afrikaans", "af"), |
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Language("Albanian", "sq"), |
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Language("Amharic", "am"), |
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Language("Arabic", "ar"), |
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Language("Armenian", "hy"), |
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Language("Asturian", "ast"), |
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Language("Azerbaijani", "az"), |
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Language("Bashkir", "ba"), |
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Language("Belarusian", "be"), |
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Language("Bulgarian", "bg"), |
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Language("Bengali", "bn"), |
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Language("Breton", "br"), |
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Language("Bosnian", "bs"), |
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Language("Burmese", "my"), |
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Language("Catalan", "ca"), |
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Language("Cebuano", "ceb"), |
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Language("Chinese","zh"), |
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Language("Croatian","hr"), |
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Language("Czech","cs"), |
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Language("Danish","da"), |
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Language("Dutch","nl"), |
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Language("English","en"), |
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Language("Estonian","et"), |
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Language("Fulah","ff"), |
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Language("Finnish","fi"), |
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Language("French","fr"), |
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Language("Western Frisian","fy"), |
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Language("Gaelic","gd"), |
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Language("Galician","gl"), |
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Language("Georgian","ka"), |
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Language("German","de"), |
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Language("Greek","el"), |
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Language("Gujarati","gu"), |
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Language("Hausa","ha"), |
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Language("Hebrew","he"), |
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Language("Hindi","hi"), |
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Language("Haitian","ht"), |
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Language("Hungarian","hu"), |
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Language("Irish","ga"), |
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Language("Indonesian","id"), |
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Language("Igbo","ig"), |
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Language("Iloko","ilo"), |
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Language("Icelandic","is"), |
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Language("Italian","it"), |
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Language("Japanese","ja"), |
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Language("Javanese","jv"), |
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Language("Kazakh","kk"), |
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Language("Central Khmer","km"), |
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Language("Kannada","kn"), |
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Language("Korean","ko"), |
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Language("Luxembourgish","lb"), |
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Language("Ganda","lg"), |
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Language("Lingala","ln"), |
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Language("Lao","lo"), |
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Language("Lithuanian","lt"), |
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Language("Latvian","lv"), |
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Language("Malagasy","mg"), |
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Language("Macedonian","mk"), |
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Language("Malayalam","ml"), |
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Language("Mongolian","mn"), |
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Language("Marathi","mr"), |
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Language("Malay","ms"), |
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Language("Nepali","ne"), |
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Language("Norwegian","no"), |
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Language("Northern Sotho","ns"), |
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Language("Occitan","oc"), |
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Language("Oriya","or"), |
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Language("Panjabi","pa"), |
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Language("Persian","fa"), |
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Language("Polish","pl"), |
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Language("Pushto","ps"), |
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Language("Portuguese","pt"), |
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Language("Romanian","ro"), |
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Language("Russian","ru"), |
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Language("Sindhi","sd"), |
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Language("Sinhala","si"), |
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Language("Slovak","sk"), |
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Language("Slovenian","sl"), |
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Language("Spanish","es"), |
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Language("Somali","so"), |
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Language("Serbian","sr"), |
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Language("Serbian (cyrillic)","sr"), |
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Language("Serbian (latin)","sr"), |
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Language("Swati","ss"), |
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Language("Sundanese","su"), |
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Language("Swedish","sv"), |
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Language("Swahili","sw"), |
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Language("Tamil","ta"), |
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Language("Thai","th"), |
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Language("Tagalog","tl"), |
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Language("Tswana","tn"), |
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Language("Turkish","tr"), |
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Language("Ukrainian","uk"), |
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Language("Urdu","ur"), |
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Language("Uzbek","uz"), |
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Language("Vietnamese","vi"), |
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Language("Welsh","cy"), |
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Language("Wolof","wo"), |
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Language("Xhosa","xh"), |
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Language("Yiddish","yi"), |
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Language("Yoruba","yo"), |
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Language("Zulu","zu"), |
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] |
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d_lang = lang_id[21] |
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def trans_page(input,trg): |
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src_lang = d_lang.code |
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for lang in lang_id: |
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if lang.name == trg: |
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trg_lang = lang.code |
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if trg_lang != src_lang: |
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tokenizer.src_lang = src_lang |
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with torch.no_grad(): |
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encoded_input = tokenizer(input, return_tensors="pt").to(device) |
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generated_tokens = model.generate(**encoded_input, forced_bos_token_id=tokenizer.get_lang_id(trg_lang)) |
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translated_text = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0] |
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else: |
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translated_text=input |
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pass |
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return translated_text |
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def trans_to(input,src,trg): |
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for lang in lang_id: |
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if lang.name == trg: |
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trg_lang = lang.code |
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for lang in lang_id: |
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if lang.name == src: |
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src_lang = lang.code |
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if trg_lang != src_lang: |
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tokenizer.src_lang = src_lang |
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with torch.no_grad(): |
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encoded_input = tokenizer(input, return_tensors="pt").to(device) |
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generated_tokens = model.generate(**encoded_input, forced_bos_token_id=tokenizer.get_lang_id(trg_lang)) |
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translated_text = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0] |
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else: |
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translated_text=input |
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pass |
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return translated_text |
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md1 = "Translate - 100 Languages" |
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with gr.Blocks() as transbot: |
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with gr.Row(): |
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gr.Column() |
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with gr.Column(): |
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with gr.Row(): |
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t_space = gr.Dropdown(label="Translate Space to:", choices=[l.name for l in lang_id], value="English") |
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t_submit = gr.Button("Translate Space") |
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gr.Column() |
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with gr.Row(): |
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gr.Column() |
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with gr.Column(): |
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md = gr.Markdown("""<h1><center>Translate - 100 Languages</center></h1><h4><center>Translation may not be accurate</center></h4>""") |
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with gr.Row(): |
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lang_from = gr.Dropdown(label="From:", choices=[l.name for l in lang_id],value="English") |
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lang_to = gr.Dropdown(label="To:", choices=[l.name for l in lang_id],value="Chinese") |
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submit = gr.Button("Go") |
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with gr.Row(): |
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with gr.Column(): |
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message = gr.Textbox(label="Prompt",placeholder="Enter Prompt",lines=4) |
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translated = gr.Textbox(label="Translated",lines=4,interactive=False) |
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gr.Column() |
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t_submit.click(trans_page,[md,t_space],[md]) |
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submit.click(trans_to, inputs=[message,lang_from,lang_to], outputs=[translated]) |
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transbot.queue(concurrency_count=20) |
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transbot.launch() |
