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:
# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download init_decoder_quant.onnx from visheratin/t5-efficient-tiny-grammar-correction: direct link, hf CLI and curl.
- Browser
- Download file 21 MB
-
https://huggingface.co/visheratin/t5-efficient-tiny-grammar-correction/resolve/refs%2Fpr%2F2/init_decoder_quant.onnx
- Command line
-
hf download hf://visheratin/t5-efficient-tiny-grammar-correction@refs/pr/2/init_decoder_quant.onnx
-
curl -L -o init_decoder_quant.onnx https://huggingface.co/visheratin/t5-efficient-tiny-grammar-correction/resolve/refs%2Fpr%2F2/init_decoder_quant.onnx
21 MB
- Xet hash:
- 207731a5689e989ed5be326f8af687311591cc1dd371f50e82d7bc5576144b30
- Size of remote file:
- 21 MB
- SHA256:
- 472a1609d7cc004424826ed61dc99a59dc7ec07d9c43e9394fbeb3595734a596
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