Instructions to use DaviadiAF/T5-Small_AbsSumm_XSumCNN_1e-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DaviadiAF/T5-Small_AbsSumm_XSumCNN_1e-2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("DaviadiAF/T5-Small_AbsSumm_XSumCNN_1e-2") model = AutoModelForSeq2SeqLM.from_pretrained("DaviadiAF/T5-Small_AbsSumm_XSumCNN_1e-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from DaviadiAF/T5-Small_AbsSumm_XSumCNN_1e-2: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/DaviadiAF/T5-Small_AbsSumm_XSumCNN_1e-2/resolve/main/training_args.bin
- Command line
-
hf download hf://DaviadiAF/T5-Small_AbsSumm_XSumCNN_1e-2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/DaviadiAF/T5-Small_AbsSumm_XSumCNN_1e-2/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- afac3463c2b1d6e60c55597cd77f90d5b98d74feb62d3ab439a686b521cb5267
- Size of remote file:
- 4.73 kB
- SHA256:
- ed66215cd0ab3d7487fbe33848d1883237bc7b8ff868f4d070b93540826e31e2
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