Instructions to use uclanlp/plbart-single_task-static-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/plbart-single_task-static-summarization with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uclanlp/plbart-single_task-static-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("uclanlp/plbart-single_task-static-summarization", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from uclanlp/plbart-single_task-static-summarization: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/uclanlp/plbart-single_task-static-summarization/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://uclanlp/plbart-single_task-static-summarization/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/uclanlp/plbart-single_task-static-summarization/resolve/main/pytorch_model.bin
557 MB
- Xet hash:
- 0acbd51279f25db47901d3f388dd03c707457f7b6d7219cf0132509927902b77
- Size of remote file:
- 557 MB
- SHA256:
- f55af17b318aeb75c5fac1e5e4bd2dd0930658b5512cec3e2862c4baa65dc3f9
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