Instructions to use circlemachinelearning/bart-email-multitask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use circlemachinelearning/bart-email-multitask with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("circlemachinelearning/bart-email-multitask") model = AutoModelForSeq2SeqLM.from_pretrained("circlemachinelearning/bart-email-multitask", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6ea18cdd72e00bfd140f20503edcd58710f35977a6020a39f74f3634643a1d5
- Size of remote file:
- 3.25 GB
- SHA256:
- 374e81646506ec785e96925a53b43bcde0358a1c71b2b55faf65745451ec9335
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.