Transformers
PyTorch
ONNX
English
t5
text2text-generation
grammar-correction
text-generation-inference
Instructions to use visheratin/t5-efficient-tiny-grammar-correction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use visheratin/t5-efficient-tiny-grammar-correction with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("visheratin/t5-efficient-tiny-grammar-correction") model = AutoModelForSeq2SeqLM.from_pretrained("visheratin/t5-efficient-tiny-grammar-correction") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfceb843240f07ad2ae2368a8beb261cc9180aabe2fb69ec8702f359d48f71a4
- Size of remote file:
- 80.5 MB
- SHA256:
- eb52a9f6cb326cb1908b486c04e089dfd18668e91e6ebf3f49fcfce3d60e6b0c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.