Instructions to use seop/summary_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seop/summary_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("seop/summary_model") model = AutoModelForSeq2SeqLM.from_pretrained("seop/summary_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from seop/summary_model: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/seop/summary_model/resolve/main/training_args.bin
- Command line
-
hf download hf://seop/summary_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/seop/summary_model/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 1794cd375b4aec0e118045687c12ed255ebe3f69e1db2ae3f34a78624e474efc
- Size of remote file:
- 4.09 kB
- SHA256:
- 37e43e2d0f3bb12a4a419591e94980a932fe5fddad113e18c1eb86828a172fb8
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