Instructions to use fenffef/t5-base-correct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fenffef/t5-base-correct with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("fenffef/t5-base-correct") model = AutoModelForSeq2SeqLM.from_pretrained("fenffef/t5-base-correct", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32679d5842a52efb65a12268aa8ccd0c4876d389b5f560ae07494eb7a387f653
- Size of remote file:
- 4.27 kB
- SHA256:
- 05da86afae2c049b66aac129b0f8c42386c3f3e788547ed97b29c03b60a53c24
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.