Instructions to use ModelTC/bart-base-xsum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-xsum with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-xsum") model = AutoModelForSeq2SeqLM.from_pretrained("ModelTC/bart-base-xsum", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from ModelTC/bart-base-xsum: direct link, hf CLI and curl.
- Browser
- Download file 1.12 GB
-
https://huggingface.co/ModelTC/bart-base-xsum/resolve/main/optimizer.pt
- Command line
-
hf download hf://ModelTC/bart-base-xsum/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/ModelTC/bart-base-xsum/resolve/main/optimizer.pt
1.12 GB
- Xet hash:
- 7127b68656096e946ae8c3b08ebee6377178c7779e75f05c106a312b3e1f7791
- Size of remote file:
- 1.12 GB
- SHA256:
- 0a196d5ba128b5eb44bc2e6151bcb783ca392b1bdd2168ed3f4f4c4a99b42dad
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