Instructions to use kykim/t5-kor-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kykim/t5-kor-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kykim/t5-kor-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kykim/t5-kor-small") model = AutoModel.from_pretrained("kykim/t5-kor-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from kykim/t5-kor-small: direct link, hf CLI and curl.
- Browser
- Download file 262 MB
-
https://huggingface.co/kykim/t5-kor-small/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://kykim/t5-kor-small/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/kykim/t5-kor-small/resolve/main/flax_model.msgpack
262 MB
- Xet hash:
- 61cd9d4babbe277765f2b47db9ba86d6670f9d9e7c80531fdb8b5999546a2e34
- Size of remote file:
- 262 MB
- SHA256:
- 65eed4300de2de61f8eec3c2c05704b63d1173e44bedd991fc1c282b5f71b4d7
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