File size: 1,108 Bytes
4421ab4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | from transformers import BartForConditionalGeneration, BartTokenizer
from transformers import pipeline
# Replace *Path* with the model path
model_path = "./fine_tune_model_bart_large_25"
# Replace **Path** with the tokenizer path
tokenizer_path = "./fine_tune_tokenizer_bart_large_25"
# Load the fine-tuned model
model = BartForConditionalGeneration.from_pretrained(model_path, ignore_mismatched_sizes=True)
# Load the tokenizer associated with the fine-tuned model
tokenizer = BartTokenizer.from_pretrained(tokenizer_path)
# Ensure the model is in evaluation mode
model.eval()
# Create a custom summarization pipeline
gen_kwargs = {"length_penalty": 1.0, "num_beams": 8, "max_length": 700}
custom_summarization_pipeline = pipeline('summarization', model=model, tokenizer=tokenizer, **gen_kwargs)
file_path = "./9.txt" # Replace with the conversation file path to check others
with open(file_path, 'r') as file:
text = file.read()
# Call the custom summarization pipeline
summary = custom_summarization_pipeline(text)
print('Summary:\n',summary[0]['summary_text'])
|