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# This file is .....
# Author: Hanbin Wang
# Date: 2023/4/18
import transformers
import streamlit as st
from PIL import Image
from transformers import RobertaTokenizer, T5ForConditionalGeneration
from transformers import pipeline
def main():
# `st.set_page_config` is used to display the default layout width, the title of the app, and the emoticon in the browser tab.
st.set_page_config(
layout="centered", page_title="MaMaL-Com Demo(代码补全)", page_icon="❄️"
)
c1, c2 = st.columns([0.32, 2])
# The snowflake logo will be displayed in the first column, on the left.
with c1:
st.image(
"./panda.png",
width=100,
)
# The heading will be on the right.
with c2:
st.caption("")
st.title("MaMaL-Com(代码补全)")
############ SIDEBAR CONTENT ############
st.sidebar.image("./panda.png",width=270)
st.sidebar.markdown("---")
st.sidebar.write(
"""
## 使用方法：
在【输入】文本框输入未完成的代码，点击【补全】按钮,即会显示补全的代码。
"""
)
st.sidebar.write(
"""
## 注意事项：
1）APP托管在外网上，请确保您可以全局科学上网。
2）您可以下载[MaMaL-Com](https://huggingface.co/hanbin/MaMaL-Com)模型，本地测试。（无需科学上网）
"""
)
st.sidebar.markdown("---")
# Let's add some info about the app to the sidebar.
st.sidebar.write(
"""
App 由 东北大学NLP课小组成员创建， 使用 [Streamlit](https://streamlit.io/)🎈 和 [HuggingFace](https://huggingface.co/inference-api)'s [MaMaL-Com](https://huggingface.co/hanbin/MaMaL-Com) 模型.
"""
)
st.write(
"> **Tip：** 首次运行需要加载模型，可能需要一定的时间！"
)
st.write(
"> **Tip：** 该Demo使用了Hugging Face 的 Pipeline,可能需要网络非常顺畅"
)
# model, tokenizer = load_model("hanbin/MaMaL-Gen")
st.write("### 输入：")
input = st.text_area("", height=200)
button = st.button('补全')
st.write("### 输出：")
generator = pipeline('text-generation', model="E:\DenseRetrievalGroup\卢帅学长ckpt\py150_model\checkpoint")
output = generator(input)
# code = '''def hello():
# print("Hello, Streamlit!")'''
if button:
st.code(output, language='python')
else:
st.write('')
if __name__ == '__main__':
main() |