File size: 1,106 Bytes
2fbe064 a5c6602 2fbe064 a5c6602 2fbe064 a5c6602 2fbe064 a5c6602 2fbe064 a5c6602 2fbe064 a5c6602 2fbe064 a5c6602 2fbe064 a5c6602 2fbe064 |
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 28 29 30 31 32 33 34 35 36 37 38 |
import gradio as gr
from paddlenlp.transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen2-0.5B")
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2-0.5B", dtype="float32")
def inference(input_text):
print(input_text)
print(type(input_text))
input_features = tokenizer(input_text, return_tensors="pd")
outputs = model.generate(**input_features, max_new_tokens=128)#max_length=128)
output_text = tokenizer.batch_decode(outputs[0], skip_special_tokens=True)[0]
return output_text
title = 'PaddlePaddle Meets LLM'
description = 'What is special: underlying execution is using PaddlePaddle and PaddleNLP!'
article = "<p style='text-align: center'> PaddleNLP <a href='https://github.com/PaddlePaddle/PaddleNLP'>Github Repo</a></p>"
examples = ['请自我介绍一下。', '今天吃什么好呢？']
demo = gr.Interface(
inference,
inputs="text",
outputs="text",
title=title,
description=description,
article=article,
examples=examples,
)
if __name__ == "__main__":
demo.launch()
|