Instructions to use ahmeshaf/ecb_tagger_seq2seq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ahmeshaf/ecb_tagger_seq2seq with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ahmeshaf/ecb_tagger_seq2seq") model = AutoModelForSeq2SeqLM.from_pretrained("ahmeshaf/ecb_tagger_seq2seq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1248e66b7da77efe3919dd764c55b06f1c4f7df7b8cc04f0283938c28b16e1c
- Size of remote file:
- 6.71 kB
- SHA256:
- 3d724b3b5ce66aa92dfa1552b1696860da1ef1ee9b6cfbe7985ef4cb3d74dcac
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.