Instructions to use Suva/uptag-keyphrase-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Suva/uptag-keyphrase-model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Suva/uptag-keyphrase-model") model = AutoModelForSeq2SeqLM.from_pretrained("Suva/uptag-keyphrase-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec5bde2ca87f78b269ca76093e2b30677a35d7c3049bcab745d30accd5ee6c03
- Size of remote file:
- 892 MB
- SHA256:
- 3548b7c6e7b729e09d006886aba69b0eccb0d90340d1828494fab0359ddeb4a2
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