Instructions to use mingu/mt5-base-finetuned-korquad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mingu/mt5-base-finetuned-korquad with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mingu/mt5-base-finetuned-korquad") model = AutoModelForSeq2SeqLM.from_pretrained("mingu/mt5-base-finetuned-korquad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2622f36db30139ba63e07e5473f0206e0e06d1f4bbde8efda8488c830f50b09
- Size of remote file:
- 2.33 GB
- SHA256:
- bd9553d6d16acfed4c0985130c9d7aad35aaa749efe63a2f97c97de139d71076
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.