Instructions to use SyedShaheer/pegasus-xsum_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SyedShaheer/pegasus-xsum_tuned with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SyedShaheer/pegasus-xsum_tuned") model = AutoModelForSeq2SeqLM.from_pretrained("SyedShaheer/pegasus-xsum_tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SyedShaheer/pegasus-xsum_tuned: direct link, hf CLI and curl.
- Browser
- Download file 2.28 GB
-
https://huggingface.co/SyedShaheer/pegasus-xsum_tuned/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SyedShaheer/pegasus-xsum_tuned/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SyedShaheer/pegasus-xsum_tuned/resolve/main/pytorch_model.bin
2.28 GB
- Xet hash:
- 4ba318e5e7a9dfd61a44b7d967360dce52468e6588147aae2dbf5915ce0d48a8
- Size of remote file:
- 2.28 GB
- SHA256:
- 3f281e6e9e1802277072cdc3c786879235bb2d618e188460223e77dedf31160b
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