Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models
Paper • 1610.02424 • Published • 1
How to use alexrink/Pegasus_CNN_VTSSum_5epochs with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "summarization" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline
pipe = pipeline("summarization", model="alexrink/Pegasus_CNN_VTSSum_5epochs") # Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("alexrink/Pegasus_CNN_VTSSum_5epochs")
model = AutoModelForSeq2SeqLM.from_pretrained("alexrink/Pegasus_CNN_VTSSum_5epochs")google/pegasus-cnn_dailymail trained on sample of VT-SSum (https://github.com/Dod-o/VT-SSum; https://arxiv.org/pdf/1610.02424.pdf)
Sample consists of 600 train, 200 validation, 200 test using categories Computer Science, Data Science, Mathematics