Instructions to use debbiesoon/bart_large_summarise with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use debbiesoon/bart_large_summarise with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("debbiesoon/bart_large_summarise") model = AutoModelForSeq2SeqLM.from_pretrained("debbiesoon/bart_large_summarise", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7bd12714acd4307ea6a89b7236ce0eeb2506345778bcf82d668aff63b1afeddd
- Size of remote file:
- 3.44 kB
- SHA256:
- b6dde7b4c355b7331a4bb2c917aedf83455172ee3939b405dfeded4153e75f7a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.