Instructions to use Seonguk/textSummarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Seonguk/textSummarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Seonguk/textSummarization") model = AutoModelForSeq2SeqLM.from_pretrained("Seonguk/textSummarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Seonguk/textSummarization: direct link, hf CLI and curl.
- Browser
- Download file 682 kB
-
https://huggingface.co/Seonguk/textSummarization/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://Seonguk/textSummarization@refs/pr/1/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Seonguk/textSummarization/resolve/refs%2Fpr%2F1/tokenizer.json
682 kB
File too large to display, you can check the raw version instead.