Transformers
PyTorch
TensorFlow
JAX
Safetensors
Korean
English
t5
text2text-generation
text-generation-inference
Instructions to use KETI-NLP/ke-t5-large-newslike with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KETI-NLP/ke-t5-large-newslike with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KETI-NLP/ke-t5-large-newslike") model = AutoModelForSeq2SeqLM.from_pretrained("KETI-NLP/ke-t5-large-newslike", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from KETI-NLP/ke-t5-large-newslike: direct link, hf CLI and curl.
- Browser
- Download file 3.13 GB
-
https://huggingface.co/KETI-NLP/ke-t5-large-newslike/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://KETI-NLP/ke-t5-large-newslike/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/KETI-NLP/ke-t5-large-newslike/resolve/main/flax_model.msgpack
3.13 GB
- Xet hash:
- 3cc6339184de3d4432811cb83deecdfb77cd2d32810259907953f9b33defa77a
- Size of remote file:
- 3.13 GB
- SHA256:
- e1af5bcc511a801a24a04c5c4e1b8133c89fbab8ef4cc4a79a6882f37f1ad855
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.