Instructions to use sangmini/sentence_split_mini_kobart-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sangmini/sentence_split_mini_kobart-base-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sangmini/sentence_split_mini_kobart-base-v2") model = AutoModelForSeq2SeqLM.from_pretrained("sangmini/sentence_split_mini_kobart-base-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from sangmini/sentence_split_mini_kobart-base-v2: direct link, hf CLI and curl.
- Browser
- Download file 991 MB
-
https://huggingface.co/sangmini/sentence_split_mini_kobart-base-v2/resolve/main/optimizer.pt
- Command line
-
hf download hf://sangmini/sentence_split_mini_kobart-base-v2/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/sangmini/sentence_split_mini_kobart-base-v2/resolve/main/optimizer.pt
991 MB
- Xet hash:
- bf23e778061d4c0001be5d2ff7cf3b9c90f84e6c2de0ab6f29cd504b2a7537ca
- Size of remote file:
- 991 MB
- SHA256:
- 83262f26b22348a126b62a2f8396b525be29f661c837495b9562919da9c2470b
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