Instructions to use YasirAbdali/bart-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YasirAbdali/bart-summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("YasirAbdali/bart-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("YasirAbdali/bart-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from YasirAbdali/bart-summarization: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/YasirAbdali/bart-summarization/resolve/main/training_args.bin
- Command line
-
hf download hf://YasirAbdali/bart-summarization/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/YasirAbdali/bart-summarization/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- f928f9af4fcbdd00c33e89467f371341f36e35e6867458649b6b1cc975a7cf01
- Size of remote file:
- 5.24 kB
- SHA256:
- c8e9265ceba087ff7968c26c702d805cf1d4e72152b6dc964f02fbb1d925fb46
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