Instructions to use omar47/bart-base-summarization1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omar47/bart-base-summarization1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("omar47/bart-base-summarization1") model = AutoModelForSeq2SeqLM.from_pretrained("omar47/bart-base-summarization1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from omar47/bart-base-summarization1: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/omar47/bart-base-summarization1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://omar47/bart-base-summarization1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/omar47/bart-base-summarization1/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 6e8ef7ab2ca8f16b46898a4cfb7f60ba5fc8c48022c93fb330a93acc72e17432
- Size of remote file:
- 558 MB
- SHA256:
- b7d64f7526a156e2561096a84eaf07cdc6bba41c8049f7196e4ebf06a5077aee
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