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from transformers import AutoTokenizer, AutoModelForCausalLM | |
from transformers import pipeline | |
tokenizer = AutoTokenizer.from_pretrained("Imran1/gpt2-urdu-news") | |
model = AutoModelForCausalLM.from_pretrained("Imran1/gpt2-urdu-news") | |
pipe = pipeline('text-generation',model=model, tokenizer=tokenizer) | |
def text_generate(text): | |
generate_text = pipe(f"{text}", max_length = 200,top_k=200, temperature=0.7, top_p=0.95) | |
return generate_text[0]['generated_text'] | |
import gradio as gr | |
exmp=["درمدی قیمتوں میں","ایک فیصلے میں کہا کہ"] | |
gr.Interface(fn=text_generate, inputs="text", outputs="text", examples=exmp,title= "FINE TUNE GPT2 FOR URDU NEWS TEXT GENERATION").launch() |