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Runtime error
| import pandas as pd | |
| import numpy as np | |
| import gradio as gr | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| import nltk | |
| nltk.download('punkt') | |
| checkpoint = "sshleifer/distilbart-cnn-12-6" | |
| tokenizer = AutoTokenizer.from_pretrained(checkpoint) | |
| model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint) | |
| def summarize_sentence(file, column): | |
| df = pd.read_csv(file.name) | |
| sentences = nltk.tokenize.sent_tokenize(df[column].values[0]) | |
| length = 0 | |
| chunk = "" | |
| chunks = [] | |
| count = -1 | |
| for sentence in sentences: | |
| count +=1 | |
| combined_length = len(tokenizer.tokenize(sentence)) + length | |
| if combined_length <= tokenizer.max_len_single_sentence: | |
| chunk += sentence + " " | |
| length = combined_length | |
| if count == len(sentences) -1: | |
| chunks.append(chunk) | |
| else: | |
| chunks.append(chunk) | |
| length = 0 | |
| chunk = "" | |
| chunk += sentence + " " | |
| length = len(tokenizer.tokenize(sentence)) | |
| inputs = [tokenizer(chunk, return_tensors='pt') for chunk in chunks] | |
| summary = '' | |
| for input in inputs: | |
| output = model.generate(**input) | |
| summary += (tokenizer.decode(*output, skip_special_tokens=True)) | |
| return (summary.replace('.<n>', '.\n')) | |
| demo = gr.Interface(summarize_sentence, | |
| inputs=[gr.inputs.File(label="CSV File", optional=False), "text"], | |
| outputs=[gr.outputs.Textbox(label="Summary")]) | |
| if __name__ == "__main__": | |
| demo.launch(debug=True) | |