Instructions to use uclanlp/plbart-single_task-en_python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/plbart-single_task-en_python with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uclanlp/plbart-single_task-en_python") model = AutoModelForSeq2SeqLM.from_pretrained("uclanlp/plbart-single_task-en_python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from uclanlp/plbart-single_task-en_python: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/uclanlp/plbart-single_task-en_python/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://uclanlp/plbart-single_task-en_python@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/uclanlp/plbart-single_task-en_python/resolve/refs%2Fpr%2F1/model.safetensors
557 MB
- Xet hash:
- 58b241818f23f911562c8befafc5b099370050cd6952c55123d80e370718f1c7
- Size of remote file:
- 557 MB
- SHA256:
- d13e4d75c52647d5db0ebe39120c4dfa8f83cf24281ab67bb21789f21589fea3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.