Instructions to use MohamedHesham/bart_base_subset_cnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MohamedHesham/bart_base_subset_cnn with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("MohamedHesham/bart_base_subset_cnn") model = AutoModelForSeq2SeqLM.from_pretrained("MohamedHesham/bart_base_subset_cnn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from MohamedHesham/bart_base_subset_cnn: direct link, hf CLI and curl.
- Browser
- Download file 558 MB
-
https://huggingface.co/MohamedHesham/bart_base_subset_cnn/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://MohamedHesham/bart_base_subset_cnn/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/MohamedHesham/bart_base_subset_cnn/resolve/main/pytorch_model.bin
558 MB
- Xet hash:
- 0fff621ecafe093c8141812d05e05441200b612f50cfd97934a3f0087a7ac659
- Size of remote file:
- 558 MB
- SHA256:
- 35a8351dfe0363d0c3b1430693d64f1074bb6657c350f8f4ebc3ee349210c264
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