Duplicate from SameerR007/abstractive_summarization

Co-authored-by: Sameer <SameerR007@users.noreply.huggingface.co>

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README.md

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+---
+title: Abstractive Summarization
+emoji: 🏢
+colorFrom: blue
+colorTo: pink
+sdk: gradio
+sdk_version: 3.23.0
+app_file: app.py
+pinned: false
+duplicated_from: SameerR007/abstractive_summarization
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+from transformers import PegasusForConditionalGeneration
+from transformers import PegasusTokenizer
+from transformers import pipeline
+
+model_name = "google/pegasus-xsum"
+pegasus_tokenizer = PegasusTokenizer.from_pretrained(model_name)
+def summarize(input_text):
+  nwords=len(input_text.split(" "))
+  # Define summarization pipeline 
+  summarizer = pipeline("summarization", model=model_name, tokenizer=pegasus_tokenizer,min_length=int(nwords/10)+20, max_length=int(nwords/5+20), framework="pt")
+  summary=summarizer(input_text)[0]['summary_text']
+  return(summary)
+gr.Interface(fn=summarize,inputs=gr.inputs.Textbox(placeholder="Paste the text to be summarized here..."),outputs="textbox").launch();

requirements.txt

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+sentencepiece
+transformers
+torch