EdinburghNLP/xsum
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How to use mrm8488/roberta-med-small_shared-finetuned-bbc_xsum-summarization 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="mrm8488/roberta-med-small_shared-finetuned-bbc_xsum-summarization") # Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("mrm8488/roberta-med-small_shared-finetuned-bbc_xsum-summarization")
model = AutoModelForSeq2SeqLM.from_pretrained("mrm8488/roberta-med-small_shared-finetuned-bbc_xsum-summarization")Shared RoBERTa2RoBERTa (med-small) Summarization with 🤗EncoderDecoder Framework
This model is a warm-started RoBERTaShared (med-small) model fine-tuned on the BBC XSum summarization dataset.