Instructions to use buscon/EducativeCS2023_bart-base-summarizationNew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use buscon/EducativeCS2023_bart-base-summarizationNew with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("buscon/EducativeCS2023_bart-base-summarizationNew") model = AutoModelForSeq2SeqLM.from_pretrained("buscon/EducativeCS2023_bart-base-summarizationNew", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8db963fb8170384dc53993dc1a8422822267c692955b4a5e851bf1126424156
- Size of remote file:
- 558 MB
- SHA256:
- cb6b6b63c23c2b8f3c03e6e467abc146774a19ef6d38b1b6b354d2be79937b05
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