Duplicate from chinhon/headline_writer

Co-authored-by: Chua chin Hon <[email protected]>

.gitattributes

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README.md

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+---
+title: Headline_writer
+emoji: 👁
+colorFrom: pink
+colorTo: purple
+sdk: gradio
+app_file: app.py
+pinned: false
+duplicated_from: chinhon/headline_writer
+---
+
+# Configuration
+
+`title`: _string_  
+Display title for the Space
+
+`emoji`: _string_  
+Space emoji (emoji-only character allowed)
+
+`colorFrom`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+
+`colorTo`: _string_  
+Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
+
+`sdk`: _string_  
+Can be either `gradio` or `streamlit`
+
+`sdk_version` : _string_  
+Only applicable for `streamlit` SDK.  
+See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
+
+`app_file`: _string_  
+Path to your main application file (which contains either `gradio` or `streamlit` Python code).  
+Path is relative to the root of the repository.
+
+`pinned`: _boolean_  
+Whether the Space stays on top of your list.

app.py

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+import gradio as gr
+import re
+
+from transformers import (
+    AutoTokenizer,
+    AutoModelForSeq2SeqLM,
+)
+
+def clean_text(text):
+    text = text.encode("ascii", errors="ignore").decode(
+        "ascii"
+    )  # remove non-ascii, Chinese characters
+    text = re.sub(r"http\S+", "", text)
+    text = re.sub(r"\n", " ", text)
+    text = re.sub(r"\n\n", " ", text)
+    text = re.sub(r"\t", " ", text)
+    text = re.sub(r"ADVERTISEMENT", " ", text)
+    text = text.strip(" ")
+    text = re.sub(
+        " +", " ", text
+    ).strip()  # get rid of multiple spaces and replace with a single
+    return text
+
+
+model_name = "chinhon/pegasus-newsroom-headline_writer_57k"
+
+def headline_writer(text):
+    input_text = clean_text(text)
+
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+    with tokenizer.as_target_tokenizer():
+        batch = tokenizer(
+            input_text,
+            truncation=True,
+            padding="longest",
+            return_tensors="pt",
+        )
+
+    raw_write = model.generate(**batch)
+
+    headline = tokenizer.batch_decode(
+        raw_write, skip_special_tokens=True, min_length=200, length_penalty=50.5
+    )
+
+    return headline[0]
+
+
+gradio_ui = gr.Interface(
+    fn=headline_writer,
+    title="Generate News Headlines with AI",
+    description="Too busy or tired to write a headline? Try this instead.",
+    inputs=gr.inputs.Textbox(
+        lines=20, label="Paste the first few paras of your news story here"
+    ),
+    outputs=gr.outputs.Textbox(label="Suggested Headline"),
+    theme="darkdefault"
+)
+
+gradio_ui.launch(enable_queue=True)

requirements.txt

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+gradio
+regex
+torch
+transformers