Instructions to use JulianPJ/TR_BART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JulianPJ/TR_BART with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("JulianPJ/TR_BART") model = AutoModelForSeq2SeqLM.from_pretrained("JulianPJ/TR_BART", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from JulianPJ/TR_BART: direct link, hf CLI and curl.
- Browser
- Download file 1.02 GB
-
https://huggingface.co/JulianPJ/TR_BART/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://JulianPJ/TR_BART/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/JulianPJ/TR_BART/resolve/main/pytorch_model.bin
1.02 GB
- Xet hash:
- 0c539a79a8f22ede2e43d723519d82490fb43528feb02c6a629beebb8da96902
- Size of remote file:
- 1.02 GB
- SHA256:
- a724e3ca5329eba8b384ec05ec6a993fbdba039b7f6ccb3e1bc225bcf0827ff0
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