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from transformers import AutoTokenizer, AutoModelWithMLHead | |
import gradio as gr | |
model_name = "deep-learning-analytics/wikihow-t5-small" | |
model = AutoModelWithMLHead.from_pretrained(model_name) | |
text2text_tokenizer = AutoTokenizer.from_pretrained(model_name) | |
def text2text(paragraph): | |
text = paragraph.strip().replace("\n", "") | |
token_text = text2text_tokenizer.encode(text, return_tensors="pt") | |
token_ids = model.generate(token_text, max_length=250, num_beams=5, repetition_penality=2.5, early_stopping=True) | |
response = text2text_tokenizer.decode(token_ids[0], skip_special_tokens=True) | |
return response | |
in_para = gr.Textbox(lines=10, label="Paragraph", placeholder="Copy paragraph") | |
out = gr.Textbox(lines=1, label="Summary") | |
gr.Interface(text2text, inputs=in_para, outputs=out) |