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import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("facebook/bart-base")
infer = AutoModelForSeq2SeqLM.from_pretrained("Qilex/bart-largeEN-ME")
def translate(sentence):
input_ids = tokenizer(sentence, return_tensors="pt").input_ids
outputs = infer.generate(input_ids, max_new_tokens = len(sentence.split(' '))*10)
return tokenizer.decode(outputs[0], skip_special_tokens=True)
def translate_multiline(sentence):
# if len(sentence.split()) > 300:
# print('Please insert less text')
if '\n' in sentence:
lines = sentence.split('\n')
translated_lines = [translate(line) for line in lines if len(line) > 0]
return '\n'.join(translated_lines)
else:
return translate(sentence)
title = "Modern English to Middle English Translator"
description = """
This translator is trained on about 70,000 English/Middle English paired sentences.
<br>
It's still a work in progress.
<br>
"""
article = '''
<br>
You can improve results by removing contractions (hadn't -> had not)
'''
gr.Interface(
fn=translate_multiline,
inputs=gr.Textbox(lines=1, placeholder="Enter text to translate."),
outputs="text",
title=title,
description=description,
article = article,
).launch()
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