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")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("psyche/KoT5-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("psyche/KoT5-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11b3e7818d60eb409bef3d488a65ad41638f4ba6c243c95cb1bdf66e9166d16a
- Size of remote file:
- 1.19 GB
- SHA256:
- 401487ff591e8682703c5ccd7e34702553a063a56af20b8409eefe2e5b8cf4c5
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