| import torch | |
| from transformers import T5Tokenizer, T5ForConditionalGeneration | |
| import gradio as gr | |
| def simplify(text): | |
| model= T5ForConditionalGeneration.from_pretrained("mynti/plainly-v1") | |
| tokenizer = T5Tokenizer.from_pretrained('t5-base', model_max_length=512) | |
| device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu") | |
| model = model.to(device) | |
| preprocess_text = "simplify: " + text.strip() | |
| tokenized_text = tokenizer.encode(preprocess_text, return_tensors="pt").to(device) | |
| summary_ids = model.generate( | |
| tokenized_text, | |
| max_length=512, | |
| num_beams=2, | |
| repetition_penalty=2.0, | |
| length_penalty=0.5, | |
| early_stopping=True | |
| ) | |
| output = tokenizer.decode(summary_ids[0], skip_special_tokens=True) | |
| return output | |
| interface = gr.Interface( | |
| fn=simplify, | |
| inputs=gr.inputs.Textbox(lines=5, placeholder="Enter a sentence here..", label="Normal English"), | |
| outputs=gr.inputs.Textbox(lines=5, label="Simple English"), | |
| cache_examples=True, | |
| title="Plainlyy", | |
| description="Translates any english sentence into a simpler and easier to understand version of it.", | |
| allow_flagging="never", | |
| examples=[ | |
| "In Brazilian cities, white workers earn roughly twice as much as those of African descent.", | |
| "The other group did a ten-minute warm-up on the bike, followed by four minutes of Tabata intervals, four times a week plus one 30-minute session of steady exercise with two minutes of intervals.", | |
| "The number of minutes Americans spend on Facebook appears to be falling, too.", | |
| "Nearly 80% of young smartphone owners regularly use a social networking application, says the research firm Enders Analysis, but two-thirds use more than one.", | |
| "The growing of coca leaves is legal and licensed 12 in Bolivia." | |
| ] | |
| ) | |
| interface.launch() | |