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app.py

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+import streamlit as st
+from transformers import pipeline
+
+@st.cache(allow_output_mutation=True)
+def load_summarizer():
+     summarizer = pipeline("summarization", model="google/bigbird-pegasus-large-bigpatent")
+     return summarizer
+
+summarize = load_summarizer()
+st.title("Patent Text Summarizer")
+sentence = st.text_area('Please paste your Patent Text :', height=300)
+button = st.button("Summarize")
+
+#max = st.sidebar.slider('Select max', 50, 500, step=10, value=500)
+#min = st.sidebar.slider('Select min', 10, 100, step=10, value=100)
+#do_sample = st.sidebar.checkbox("Do sample", value=False)
+with st.spinner("Generating Patent Summary.."):
+    if button and sentence:
+        #chunks = generate_chunks(sentence)
+        res = summarize(sentence,
+                         max_length=500, 
+                         min_length=100,
+                         truncation=True,
+                         #do_sample=do_sample
+                         )
+        text = ' '.join([summ['summary_text'] for summ in res])
+        # st.write(result[0]['summary_text'])
+        st.write(text)