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from transformers import T5ForConditionalGeneration, AutoTokenizer
import gradio as gr
model_name = "google/flan-t5-large"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = T5ForConditionalGeneration.from_pretrained(model_name)
def translate(input_text, src_lang, to_lang):
prompt = f"Translate {src_lang} to {to_lang}: {input_text}"
input_ids = tokenizer(prompt, return_tensors="pt").input_ids
outputs = model.generate(input_ids, max_new_tokens=1000)
model_translation = tokenizer.decode(outputs[0])
final_translation = model_translation[5:-4]
return final_translation
languages = [
'English', 'Spanish', 'Japanese', 'Persian', 'Hindi', 'French', 'Chinese',
'Bengali', 'Gujarati', 'German', 'Telugu', 'Italian', 'Arabic', 'Polish',
'Tamil', 'Marathi', 'Malayalam', 'Oriya', 'Panjabi', 'Portuguese', 'Urdu',
'Galician', 'Hebrew', 'Korean', 'Catalan', 'Thai', 'Dutch', 'Indonesian',
'Vietnamese', 'Bulgarian', 'Filipino', 'Central Khmer', 'Lao', 'Turkish',
'Russian', 'Croatian', 'Swedish', 'Yoruba', 'Kurdish', 'Burmese', 'Malay',
'Czech', 'Finnish', 'Somali', 'Tagalog', 'Swahili', 'Sinhala', 'Kannada',
'Zhuang', 'Igbo', 'Xhosa', 'Romanian', 'Haitian', 'Estonian', 'Slovak',
'Lithuanian', 'Greek', 'Nepali', 'Assamese', 'Norwegian'
]
version = "v-0.0.1"
desc = "<h1><em>tTranslaterR</em> is a translation app powered by AI models capable of translating text between 50+ languages</h1>"
translator = gr.Interface(fn=translate,
inputs=[gr.Textbox(label="Input Text", placeholder="Input Text To Be Translated"),
gr.Dropdown(label="From",
choices=languages,
value="English",),
gr.Dropdown(label="To",
choices=languages,
value="German")],
outputs=gr.Textbox(label="Translation"),
title=f"tTranslatorR {version} model {model_name}",
description=desc
)
translator.launch()
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