Instructions to use Inria-CEDAR/WebNLG20T5B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Inria-CEDAR/WebNLG20T5B with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Inria-CEDAR/WebNLG20T5B") model = AutoModelForSeq2SeqLM.from_pretrained("Inria-CEDAR/WebNLG20T5B") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e836219d6197f476dbeabc85200c9d8c3159203ad21fe5355f0aaf5ae1751d3
- Size of remote file:
- 892 MB
- SHA256:
- 63b5da907b19e178df31810cba59e638e65ba6a22fb6ebe5bfe5f8ea74a904ff
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