Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
Korean
t5
text2text-generation
text-generation-inference
Instructions to use KETI-NLP/ke-t5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KETI-NLP/ke-t5-base with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KETI-NLP/ke-t5-base") model = AutoModelForSeq2SeqLM.from_pretrained("KETI-NLP/ke-t5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from KETI-NLP/ke-t5-base: direct link, hf CLI and curl.
- Browser
- Download file 990 MB
-
https://huggingface.co/KETI-NLP/ke-t5-base/resolve/3fdf631a2986e928ad8b22863f9da16da74d9906/flax_model.msgpack
- Command line
-
hf download hf://KETI-NLP/ke-t5-base@3fdf631a2986e928ad8b22863f9da16da74d9906/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/KETI-NLP/ke-t5-base/resolve/3fdf631a2986e928ad8b22863f9da16da74d9906/flax_model.msgpack
990 MB
- Xet hash:
- 9350d1fac14a64bfc797a66791af048b29389d089afac917d363d040fd668d18
- Size of remote file:
- 990 MB
- SHA256:
- 56f34eeb5b16d0e497b0f077ffa1ffb3a57ab16c7fe2595c96142661e0fd3978
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