Instructions to use krm/BARTkrame-abstract with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use krm/BARTkrame-abstract 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="krm/BARTkrame-abstract")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("krm/BARTkrame-abstract") model = AutoModelForSeq2SeqLM.from_pretrained("krm/BARTkrame-abstract", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- name: BARTkrame-abstract
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results: []
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- text: "Jens Peter Hansen kommer fra Danmark"
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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