Summarization
Transformers
PyTorch
Safetensors
Korean
t5
text2text-generation
text-generation-inference
Instructions to use psyche/KoT5-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use psyche/KoT5-summarization with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="psyche/KoT5-summarization")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("psyche/KoT5-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("psyche/KoT5-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from psyche/KoT5-summarization: direct link, hf CLI and curl.
- Browser
- Download file 1.19 GB
-
https://huggingface.co/psyche/KoT5-summarization/resolve/main/model.safetensors
- Command line
-
hf download hf://psyche/KoT5-summarization/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/psyche/KoT5-summarization/resolve/main/model.safetensors
1.19 GB
- Xet hash:
- 6b9978cab726166b4fc01b4028b5b1bbb400968605a93bcc033ca1195f363c7e
- Size of remote file:
- 1.19 GB
- SHA256:
- 309f085485387c8a00f798a316de7522f0d91efc0edac5d1137ce404431a852f
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