Create app.py
Browse files
app.py
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import gradio as gr
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
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import torch
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LANGS = ["kin_Latn","eng_Latn"]
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TASK = "translation"
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# CKPT = "DigitalUmuganda/Finetuned-NLLB"
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# MODELS = ["facebook/nllb-200-distilled-600M","DigitalUmuganda/Finetuned-NLLB"]
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# model = AutoModelForSeq2SeqLM.from_pretrained(CKPT)
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# tokenizer = AutoTokenizer.from_pretrained(CKPT)
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device = 0 if torch.cuda.is_available() else -1
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#general_model = AutoModelForSeq2SeqLM.from_pretrained("mbazaNLP/Nllb_finetuned_general_en_kin")
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#education_model = AutoModelForSeq2SeqLM.from_pretrained("mbazaNLP/Nllb_finetuned_education_en_kin")
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tourism_model = AutoModelForSeq2SeqLM.from_pretrained("mbazaNLP/Nllb_finetuned_tourism_en_kin")
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#MODELS = {"General model":general_model_model,"Education model":education_model,"Tourism model":tourism_model}
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#MODELS = {"Education model":education_model,"Tourism model":tourism_model}
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tokenizer = AutoTokenizer.from_pretrained("mbazaNLP/Nllb_finetuned_general_en_kin")
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# def translate(text, src_lang, tgt_lang, max_length=400):
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TASK = "translation"
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device = 0 if torch.cuda.is_available() else -1
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def translate(text, source_lang, target_lang, max_length=400):
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"""
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Translate text from source language to target language
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"""
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# src_lang = choose_language(source_lang)
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# tgt_lang= choose_language(target_lang)
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# if src_lang==None:
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# return "Error: the source langage is incorrect"
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# elif tgt_lang==None:
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# return "Error: the target language is incorrect"
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translation_pipeline = pipeline(TASK,
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model=tourism_model,
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tokenizer=tokenizer,
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src_lang=source_lang,
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tgt_lang=target_lang,
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max_length=max_length,
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device=device)
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result = translation_pipeline(text)
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return result[0]['translation_text']
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gradio_ui= gr.Interface(
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fn=translate,
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title="NLLB-Tourism EN-KIN Translation Demo",
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inputs= [
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gr.components.Textbox(label="Text"),
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gr.components.Dropdown(label="Source Language", choices=LANGS),
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gr.components.Dropdown(label="Target Language", choices=LANGS),
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# gr.components.Slider(8, 400, value=400, step=8, label="Max Length")
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],
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outputs=gr.outputs.Textbox(label="Translated text")
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)
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gradio_ui.launch()
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