Instructions to use Rumesh/txt-smp-mbart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Rumesh/txt-smp-mbart with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Rumesh/txt-smp-mbart") model = AutoModelForSeq2SeqLM.from_pretrained("Rumesh/txt-smp-mbart", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 239db0dcefe6c4a436b6036c7e7ffde713cae6830ade64f965677cf7b3b710e1
- Size of remote file:
- 2.44 GB
- SHA256:
- 000e5eb4f0b1a046245be84531582f8d4f343551723a94007f35f90f5b34c6e6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.