Instructions to use uclanlp/plbart-cs-java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/plbart-cs-java with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uclanlp/plbart-cs-java") model = AutoModelForSeq2SeqLM.from_pretrained("uclanlp/plbart-cs-java", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from uclanlp/plbart-cs-java: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/uclanlp/plbart-cs-java/resolve/ca175ce02748073c8b3813d6fe2aa1856ce9dabe/pytorch_model.bin
- Command line
-
hf download hf://uclanlp/plbart-cs-java@ca175ce02748073c8b3813d6fe2aa1856ce9dabe/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/uclanlp/plbart-cs-java/resolve/ca175ce02748073c8b3813d6fe2aa1856ce9dabe/pytorch_model.bin
557 MB
- Xet hash:
- e5a46c475355dfad58a344f2d1e65c555a1414d1b9f36a99da53e03a0376e1bb
- Size of remote file:
- 557 MB
- SHA256:
- 193729303a2ceb8bec5845505209bfcd04ac8af75c55adc12f2947c6f796d744
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