Transformers
PyTorch
Safetensors
Korean
longt5
text2text-generation
Generated from Trainer
Eval Results (legacy)
Instructions to use KETI-AIR-Downstream/long-ke-t5-base-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KETI-AIR-Downstream/long-ke-t5-base-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KETI-AIR-Downstream/long-ke-t5-base-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("KETI-AIR-Downstream/long-ke-t5-base-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from KETI-AIR-Downstream/long-ke-t5-base-summarization: direct link, hf CLI and curl.
- Browser
- Download file 4.17 MB
-
https://huggingface.co/KETI-AIR-Downstream/long-ke-t5-base-summarization/resolve/main/tokenizer.json
- Command line
-
hf download hf://KETI-AIR-Downstream/long-ke-t5-base-summarization/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/KETI-AIR-Downstream/long-ke-t5-base-summarization/resolve/main/tokenizer.json
4.17 MB
File too large to display, you can check the raw version instead.