Instructions to use brutusxu/t5-base-finetuned-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use brutusxu/t5-base-finetuned-xsum with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("brutusxu/t5-base-finetuned-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("brutusxu/t5-base-finetuned-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 44805e8e165b748a70b779b4b191bd8671f2b3a7931ae69977c57e3b4f6ab0a0
- Size of remote file:
- 1.78 GB
- SHA256:
- 8bc2457afdabd2cd385d5a14e1fedb27de31fce1927798456d159bab017b1d27
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