File size: 889 Bytes
0997170 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 |
import gradio as gr
import torch
from transformers import AutoTokenizer, T5ForConditionalGeneration
model_id = 'ksabeh/gavi'
max_input_length = 512
max_target_length = 10
model = T5ForConditionalGeneration.from_pretrained(model_id)
tokenizer = AutoTokenizer.from_pretrained(model_id)
def predict(title, category):
input = f"{title} <hl> {category} <hl>"
model_input = tokenizer(input, max_length=max_input_length, truncation=True,
padding="max_length")
model_input = {k:torch.unsqueeze(torch.tensor(v),dim=0) for k,v in model_input.items()}
predictions = model.generate(**model_input, num_beams=8, do_sample=True, max_length=10)
return tokenizer.batch_decode(predictions, skip_special_tokens=True)[0]
iface = gr.Interface(
predict,
inputs=["text", "text"],
outputs=['text'],
title="Attribute Generation",
)
iface.launch() |