Instructions to use Zohaib002/Longformer-Encoder-Decoder-LED with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zohaib002/Longformer-Encoder-Decoder-LED with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Zohaib002/Longformer-Encoder-Decoder-LED") model = AutoModelForSeq2SeqLM.from_pretrained("Zohaib002/Longformer-Encoder-Decoder-LED", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9dd98e5b786e63f53f8a8241f2ab70502664a386d641bebb4ef279941ce36995
- Size of remote file:
- 5.24 kB
- SHA256:
- d2aea0194ee6b8709781d120e5a5693cc37c33cdaf036cdf19d29a8b77bb733d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.