# 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 # @st.cache_resource # def load_model(model_name): # # load model # model = T5ForConditionalGeneration.from_pretrained("E:\DenseRetrievalGroup\卢帅学长ckpt\py150_model\checkpoint") # # load tokenizer # tokenizer = RobertaTokenizer.from_pretrained("E:\DenseRetrievalGroup\卢帅学长ckpt\py150_model\checkpoint") # return model,tokenizer 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( "images/panda.png", width=100, ) # The heading will be on the right. with c2: st.caption("") st.title("MaMaL-Gen(代码生成)") ############ SIDEBAR CONTENT ############ st.sidebar.image("images/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。 """ ) # For elements to be displayed in the sidebar, we need to add the sidebar element in the widget. # We create a text input field for users to enter their API key. # API_KEY = st.sidebar.text_input( # "Enter your HuggingFace API key", # help="Once you created you HuggingFace account, you can get your free API token in your settings page: https://huggingface.co/settings/tokens", # type="password", # ) # # # Adding the HuggingFace API inference URL. # API_URL = "https://api-inference.huggingface.co/models/valhalla/distilbart-mnli-12-3" # # # Now, let's create a Python dictionary to store the API headers. # headers = {"Authorization": f"Bearer {API_KEY}"} 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-Gen](https://huggingface.co/hanbin/MaMaL-Gen) 模型. """ ) generator = pipeline('text-generation', model="hanbin/MaMaL-Com") # model, tokenizer = load_model("hanbin/MaMaL-Gen") st.write("### 输入:") input = st.text_area("",height=200) output = generator(input) # code = '''def hello(): # print("Hello, Streamlit!")''' if st.button('补全'): st.write("### 输出:") st.code(output, language='python') else: st.write('') if __name__ == '__main__': main()