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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-large") | |
model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-large", device_map="auto", cache_dir="cache", offload_folder="offload" ) | |
def generate(input_text): | |
input_ids = tokenizer(input_text, return_tensors="pt") | |
output = model.generate(input_ids, max_length=70) | |
return tokenizer.decode(output[0], skip_special_tokens=True) | |
#@title GUI | |
import gradio as gr | |
title = "Flan T5 :)" | |
def inference(text): | |
return generate(text) | |
io = gr.Interface( | |
inference, | |
gr.Textbox(lines=3), | |
outputs=[ | |
gr.Textbox(lines=3, label="Flan T5") | |
], | |
title=title, | |
) | |
io.launch(share=False,debug=False) |