Instructions to use jgriffi/bart_abstract_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jgriffi/bart_abstract_summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jgriffi/bart_abstract_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("jgriffi/bart_abstract_summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from jgriffi/bart_abstract_summarization: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/jgriffi/bart_abstract_summarization/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://jgriffi/bart_abstract_summarization/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/jgriffi/bart_abstract_summarization/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- 1c591b8386ce464f5227634fa580dd21d80f0dae6dc52ed0e00217589a51243a
- Size of remote file:
- 1.63 GB
- SHA256:
- c22a17a6a0faca5a04b00f34498a8870ac3a8bf397cf5163242e966e8752b361
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