Instructions to use vagmi/grammar-t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vagmi/grammar-t5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vagmi/grammar-t5") model = AutoModelForSeq2SeqLM.from_pretrained("vagmi/grammar-t5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from vagmi/grammar-t5: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/vagmi/grammar-t5/resolve/main/model.safetensors
- Command line
-
hf download hf://vagmi/grammar-t5/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/vagmi/grammar-t5/resolve/main/model.safetensors
892 MB
- Xet hash:
- b4083177558345911ca2e9e0f6e5d3368d7888518f801c53a594d8818a60f24c
- Size of remote file:
- 892 MB
- SHA256:
- 4c618b8cc627ea205784fb722b4dd99a69ea94e4b5a04083021f72937d0291a1
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