Instructions to use Minata/plbart-base-finetuned-ut-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Minata/plbart-base-finetuned-ut-generator with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Minata/plbart-base-finetuned-ut-generator") model = AutoModelForSeq2SeqLM.from_pretrained("Minata/plbart-base-finetuned-ut-generator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a9c45ccf58c0b7e3f6225152019a710979678e9bd7c2d49e33a5a0e404b94dd4
- Size of remote file:
- 557 MB
- SHA256:
- 6b820159daeb5ade21aeccee782960677125fe3feddfb28ab4ed4a16870ab15a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.