Instructions to use nytkng/distilbart_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nytkng/distilbart_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="nytkng/distilbart_summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nytkng/distilbart_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("nytkng/distilbart_summarization") - Notebooks
- Google Colab
- Kaggle
File size: 84 Bytes
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datasets:
- samsum
language:
- en
tags:
- summarization
- samsum
- finetuned
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