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| #importing the necessary libraries | |
| import re | |
| import nltk | |
| from nltk.tokenize import sent_tokenize | |
| nltk.download("punkt") | |
| import gradio as gr | |
| from gradio.mix import Parallel | |
| # Defining a function to read in the text file | |
| def read_in_text(url): | |
| with open(URL, "r") as file: | |
| article = file.read() | |
| return article | |
| #Doing some text preprocessing, more will still be needed later | |
| def clean_text(text): | |
| #text = read_in_text(url) | |
| text = text.encode("ascii", errors="ignore").decode( | |
| "ascii" | |
| ) # remove non-ascii, Chinese characters | |
| text = re.sub(r"\n", " ", text) | |
| text = re.sub(r"\n\n", " ", text) | |
| text = re.sub(r"\t", " ", text) | |
| text = text.strip(" ") | |
| text = re.sub( | |
| " +", " ", text | |
| ).strip() # get rid of multiple spaces and replace with a single | |
| return text | |
| #importing the model and tokenizer for the headline generator | |
| from transformers import ( | |
| AutoTokenizer, | |
| AutoModelForSeq2SeqLM, | |
| ) | |
| #initializing the tokenizer and the model | |
| tokenizer = AutoTokenizer.from_pretrained("valurank/final_headline_generator") | |
| model = AutoModelForSeq2SeqLM.from_pretrained("valurank/final_headline_generator") | |
| #Defining a function to generate the headlines | |
| def headline_generator_2(file): | |
| input_text = file | |
| #input_text = sent_tokenize(input_text) | |
| #text = ''.join(input_text[:6]) | |
| inputs = tokenizer(input_text,truncation=True, return_tensors="pt") | |
| summary_ids = model.generate(inputs["input_ids"],min_length=20, max_length=40) | |
| summary = tokenizer.batch_decode(summary_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0] | |
| return summary | |
| #creating an interface for the headline generator using gradio | |
| demo = gr.Interface(headline_generator_2, inputs=[gr.inputs.Textbox(label="Drop your .txt file here", optional=False)], | |
| title = "HEADLINE GENERATOR", | |
| outputs=[gr.outputs.Textbox(label="Headline")], | |
| theme= "darkhuggingface") | |
| #launching the app | |
| if __name__ == "__main__": | |
| demo.launch(debug=True) |