Instructions to use NTUYG/SOTitle-java-BART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NTUYG/SOTitle-java-BART with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("NTUYG/SOTitle-java-BART") model = AutoModelForSeq2SeqLM.from_pretrained("NTUYG/SOTitle-java-BART", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from NTUYG/SOTitle-java-BART: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/NTUYG/SOTitle-java-BART/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://NTUYG/SOTitle-java-BART/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/NTUYG/SOTitle-java-BART/resolve/main/pytorch_model.bin
1.63 GB
- Xet hash:
- 38d33dfa328475596e9f64ed50a9a87c57a8e27905b2daec23480d17d5593f95
- Size of remote file:
- 1.63 GB
- SHA256:
- 207a4aec91dfe4ca63a2b3bf90abfe54b29f9084e4eb365b78339f0b826d0e27
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