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import gradio as gr | |
from transformers import pipeline | |
import torch | |
import os | |
pipe = pipeline("text-generation", model="gplsi/Aitana-6.3B", torch_dtype=torch.bfloat16, device_map="auto", | |
token=os.environ['gplsi_models']) | |
def predict(input_text): | |
generation = pipe(input_text, max_new_tokens=50, repetition_penalty=1.2, top_k=50, top_p=0.95, do_sample=True, | |
temperature=0.5, early_stopping=True, num_beams=2) | |
return generation[0] | |
gradio_app = gr.Interface( | |
predict, | |
inputs='text', | |
outputs='text', | |
title="Aitana-6.3B Text Generation", | |
) | |
if __name__ == "__main__": | |
gradio_app.launch() |