Instructions to use faprika/plbart-base-bugfixing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use faprika/plbart-base-bugfixing with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("faprika/plbart-base-bugfixing") model = AutoModelForSeq2SeqLM.from_pretrained("faprika/plbart-base-bugfixing") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9278ae809c5df1550beb1da0d777de52afab7118c5b76adbac8802cfd8b623df
- Size of remote file:
- 557 MB
- SHA256:
- 4ac4ad3e698c6f41e45c01e70c6658e66c1aa18226077b8f34f2371a3733ee74
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.