Transformers
PyTorch
ONNX
English
t5
text2text-generation
grammar-correction
text-generation-inference
Instructions to use visheratin/t5-efficient-mini-grammar-correction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use visheratin/t5-efficient-mini-grammar-correction with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("visheratin/t5-efficient-mini-grammar-correction") model = AutoModelForSeq2SeqLM.from_pretrained("visheratin/t5-efficient-mini-grammar-correction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download decoder_model.onnx from visheratin/t5-efficient-mini-grammar-correction: direct link, hf CLI and curl.
- Browser
- Download file 137 MB
-
https://huggingface.co/visheratin/t5-efficient-mini-grammar-correction/resolve/main/decoder_model.onnx
- Command line
-
hf download hf://visheratin/t5-efficient-mini-grammar-correction/decoder_model.onnx
-
curl -L -o decoder_model.onnx https://huggingface.co/visheratin/t5-efficient-mini-grammar-correction/resolve/main/decoder_model.onnx
137 MB
- Xet hash:
- 4d01127f19d1735ae3f1004ecc71c977666badff329ad3d02bb4eb262773e305
- Size of remote file:
- 137 MB
- SHA256:
- bfbc4434c9d5681e3d9f9afdc79791715b826f38297282fd5e72ba2452ed1e2d
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