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 init_decoder_model_quantized.onnx from visheratin/t5-efficient-mini-grammar-correction: direct link, hf CLI and curl.
- Browser
- Download file 36.1 MB
-
https://huggingface.co/visheratin/t5-efficient-mini-grammar-correction/resolve/main/init_decoder_model_quantized.onnx
- Command line
-
hf download hf://visheratin/t5-efficient-mini-grammar-correction/init_decoder_model_quantized.onnx
-
curl -L -o init_decoder_model_quantized.onnx https://huggingface.co/visheratin/t5-efficient-mini-grammar-correction/resolve/main/init_decoder_model_quantized.onnx
36.1 MB
- Xet hash:
- 8d6d4316d7c2e6a557beb76faeb9c9dba5ca5ea4d04efb1e7db12681d7d0a458
- Size of remote file:
- 36.1 MB
- SHA256:
- d11979f42ce0aaad68e6b59a5583632968dbe1bfebab713467c0dc2b5f079fe9
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