Instructions to use uclanlp/plbart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/plbart-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uclanlp/plbart-base") model = AutoModelForSeq2SeqLM.from_pretrained("uclanlp/plbart-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from uclanlp/plbart-base: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/uclanlp/plbart-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://uclanlp/plbart-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/uclanlp/plbart-base/resolve/main/pytorch_model.bin
557 MB
- Xet hash:
- b730210f49526238b3cdbcc8fd2c4c9e19f0ee1a691269ab272ae4060bd1d26a
- Size of remote file:
- 557 MB
- SHA256:
- 0464126e52fdfa778fb6af6577096923da2cb2ca68fa2db4df4b7824c9e0cb7c
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