Instructions to use uclanlp/plbart-multi_task-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/plbart-multi_task-python with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uclanlp/plbart-multi_task-python") model = AutoModelForSeq2SeqLM.from_pretrained("uclanlp/plbart-multi_task-python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from uclanlp/plbart-multi_task-python: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/uclanlp/plbart-multi_task-python/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://uclanlp/plbart-multi_task-python@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/uclanlp/plbart-multi_task-python/resolve/refs%2Fpr%2F1/model.safetensors
557 MB
- Xet hash:
- 23c9dfe0fa20ae8431d8372ea14ce598bcac66fcfeb9d32ee859d34bbc24f6b3
- Size of remote file:
- 557 MB
- SHA256:
- d97fb5721d2188d59211afc67a70ca14e9cf2ec62a7f34a6f42085534491d02b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.