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:
- b5cc3c55009932033e493962cd6df25bee8252ff23ba0e905ed7413ca9849021
- Size of remote file:
- 242 MB
- SHA256:
- da1a681c6910fcf9624d64ea3d93dea8b57d1f21432c064e40987fe289c264b7
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