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") - Notebooks
- Google Colab
- Kaggle
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- text: "Nous voulons que tous les êtres humains, ensemble ou pris isolément, jeunes ou vieux, riches ou pauvres, nobles ou roturiers, hommes ou femmes, puissent pleinement s'instruire et devenir des êtres achevés. Nous voulons qu'ils soient instruits parfaitement et formés non seulement sur tel ou tel point, mais également sur tout ce qui permet à l'homme de réaliser intégralement son essence"
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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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