Instructions to use gsl22/bart-samsum-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gsl22/bart-samsum-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("gsl22/bart-samsum-v1") model = AutoModelForSeq2SeqLM.from_pretrained("gsl22/bart-samsum-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gsl22/bart-samsum-v1: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/gsl22/bart-samsum-v1/resolve/main/training_args.bin
- Command line
-
hf download hf://gsl22/bart-samsum-v1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gsl22/bart-samsum-v1/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 6f1b4cdae09538ea4d07a292e5adc802897e75ac37293def56b76d63c580c122
- Size of remote file:
- 3.96 kB
- SHA256:
- 0beb1a4ad57f19461185b2f06b4371257707eb1a41cc7c54c38f07b5751a3b77
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