Instructions to use Aktsvigun/bart-base_scisummnet_6864530 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aktsvigun/bart-base_scisummnet_6864530 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Aktsvigun/bart-base_scisummnet_6864530") model = AutoModelForSeq2SeqLM.from_pretrained("Aktsvigun/bart-base_scisummnet_6864530", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Aktsvigun/bart-base_scisummnet_6864530: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/Aktsvigun/bart-base_scisummnet_6864530/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Aktsvigun/bart-base_scisummnet_6864530/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Aktsvigun/bart-base_scisummnet_6864530/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 5c98c74a083f27a98ba985dec21e4f174a9eecac727b964a38d6738f4dbac315
- Size of remote file:
- 558 MB
- SHA256:
- 23795b955c31e02a36d298c1b9ef517255132fafda35c2ee45ef7494b5d34c5d
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