Instructions to use ademax/normalize_s2t_dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ademax/normalize_s2t_dataset with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ademax/normalize_s2t_dataset") model = AutoModelForSeq2SeqLM.from_pretrained("ademax/normalize_s2t_dataset", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ademax/normalize_s2t_dataset: direct link, hf CLI and curl.
- Browser
- Download file 904 MB
-
https://huggingface.co/ademax/normalize_s2t_dataset/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ademax/normalize_s2t_dataset/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ademax/normalize_s2t_dataset/resolve/main/pytorch_model.bin
904 MB
- Xet hash:
- a3def5792791c7ecfaadd69dc75554a23c9822f83bc849ef0d7dda12469dd1b4
- Size of remote file:
- 904 MB
- SHA256:
- b23791b15e0511801ecc2749c4f1431ac013a5edea207a2f5ba8ec40d07b8bbe
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