Instructions to use Earth1221/Spelling with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Earth1221/Spelling with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Earth1221/Spelling") model = AutoModelForSeq2SeqLM.from_pretrained("Earth1221/Spelling", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Earth1221/Spelling: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/Earth1221/Spelling/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Earth1221/Spelling/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Earth1221/Spelling/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- c907c8503f85d3a4d656c677ed39ad558a188c4ac70aad8632085f94fc719cc3
- Size of remote file:
- 558 MB
- SHA256:
- 1b99bf77a995427c3c6f56c96f6721f495cdd1af87112f91e5b01db8455a15e5
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