Instructions to use paulh27/cnn_aligned_smallT5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulh27/cnn_aligned_smallT5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("paulh27/cnn_aligned_smallT5") model = AutoModelForSeq2SeqLM.from_pretrained("paulh27/cnn_aligned_smallT5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from paulh27/cnn_aligned_smallT5: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/paulh27/cnn_aligned_smallT5/resolve/a0138c8ee3433fdffcb408cf08d8d411d2544721/training_args.bin
- Command line
-
hf download hf://paulh27/cnn_aligned_smallT5@a0138c8ee3433fdffcb408cf08d8d411d2544721/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/paulh27/cnn_aligned_smallT5/resolve/a0138c8ee3433fdffcb408cf08d8d411d2544721/training_args.bin
5.11 kB
- Xet hash:
- 7d9da1830fdb92c867bc3671340d4be818c09d9200c29b735421088bd626f6a0
- Size of remote file:
- 5.11 kB
- SHA256:
- 6c0b6c6a3c7690021525a01acb7a943c0a6dd7ca7ebfbf4682908c9bcc0bdccb
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