Transformers
PyTorch
TensorFlow
JAX
Safetensors
Korean
t5
text2text-generation
text-generation-inference
Instructions to use KETI-NLP/ke-t5-base-ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KETI-NLP/ke-t5-base-ko with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KETI-NLP/ke-t5-base-ko") model = AutoModelForSeq2SeqLM.from_pretrained("KETI-NLP/ke-t5-base-ko", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download spiece.model from KETI-NLP/ke-t5-base-ko: direct link, hf CLI and curl.
- Browser
- Download file 1.47 MB
-
https://huggingface.co/KETI-NLP/ke-t5-base-ko/resolve/main/spiece.model
- Command line
-
hf download hf://KETI-NLP/ke-t5-base-ko/spiece.model
-
curl -L -o spiece.model https://huggingface.co/KETI-NLP/ke-t5-base-ko/resolve/main/spiece.model
1.47 MB
- Xet hash:
- 7a004d979866717ad5efc1c9d71efaf52a4930d2a3eedc2bdcce4e0ca42c2cd8
- Size of remote file:
- 1.47 MB
- SHA256:
- edc595fcd800672d6ef0e2aea5ba0f1dc8826471f6f40a87b70619dcc60ddd4a
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