Instructions to use omar47/bart-base-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omar47/bart-base-summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("omar47/bart-base-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("omar47/bart-base-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from omar47/bart-base-summarization: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/omar47/bart-base-summarization/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://omar47/bart-base-summarization/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/omar47/bart-base-summarization/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- bf93cfae9eb4dcf87fa37d6a5322ced74f8af276efb18afeeec00b3aa7652b07
- Size of remote file:
- 558 MB
- SHA256:
- 4fceba8ac50ec6d81231457c28dae842faf6df2d6d8c7cea3457fb73fd551e2c
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