Instructions to use lincoln/mbart-mlsum-automatic-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lincoln/mbart-mlsum-automatic-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="lincoln/mbart-mlsum-automatic-summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lincoln/mbart-mlsum-automatic-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("lincoln/mbart-mlsum-automatic-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5dca163e1be0650e95e741a46788be168217cb39ced1e3be88d4396e345ac33b
- Size of remote file:
- 2.44 GB
- SHA256:
- 59ad07c3fad3cfa1c4ebd75b101ff84296159bea678af02b67e34eaf38d22ce5
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