Instructions to use nytkng/t5_base_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nytkng/t5_base_summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nytkng/t5_base_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("nytkng/t5_base_summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nytkng/t5_base_summarization: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/nytkng/t5_base_summarization/resolve/main/training_args.bin
- Command line
-
hf download hf://nytkng/t5_base_summarization/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nytkng/t5_base_summarization/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- 804bf2256cf7daf9cd342ed7214ecea1a0fd54673afbfc847ff5283798170bc0
- Size of remote file:
- 5.05 kB
- SHA256:
- 875edaf0b675dcd6d4151c9b40a55ec59cea20934c45eb26a3a8ea7b500adbb7
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