Instructions to use royeis/T5-FlowNLG-Realizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use royeis/T5-FlowNLG-Realizer with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("royeis/T5-FlowNLG-Realizer") model = AutoModelForSeq2SeqLM.from_pretrained("royeis/T5-FlowNLG-Realizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5447a47efb576fad9b05ff69499a1c6315397dcb664fc5004010b5de9748d61c
- Size of remote file:
- 892 MB
- SHA256:
- c7c82e2ccd6bce09d682509b8c53525d13009edbabffd6e8ea559b5ac0784b9d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.