Transformers
PyTorch
Safetensors
Korean
bart
text2text-generation
KoBART
BART
Korean
QG
Question
KorQuad
Instructions to use rycont/KoQuestionBART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rycont/KoQuestionBART with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rycont/KoQuestionBART") model = AutoModelForSeq2SeqLM.from_pretrained("rycont/KoQuestionBART", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rycont/KoQuestionBART: direct link, hf CLI and curl.
- Browser
- Download file 496 MB
-
https://huggingface.co/rycont/KoQuestionBART/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rycont/KoQuestionBART/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rycont/KoQuestionBART/resolve/main/pytorch_model.bin
496 MB
- Xet hash:
- f707a2451f0b6586af97b89dd491cf81d1ede37bba874680750a30101a27e26b
- Size of remote file:
- 496 MB
- SHA256:
- c7f3e6d9c277a6198f5f8f20668fe3061474124b8e94d37f4c35dbbd35de03cb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.