Instructions to use uclanlp/plbart-multi_task-dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/plbart-multi_task-dynamic with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uclanlp/plbart-multi_task-dynamic") model = AutoModelForSeq2SeqLM.from_pretrained("uclanlp/plbart-multi_task-dynamic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from uclanlp/plbart-multi_task-dynamic: direct link, hf CLI and curl.
- Browser
- Download file 557 MB
-
https://huggingface.co/uclanlp/plbart-multi_task-dynamic/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://uclanlp/plbart-multi_task-dynamic/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/uclanlp/plbart-multi_task-dynamic/resolve/main/pytorch_model.bin
557 MB
- Xet hash:
- a3c58673dde2a1bed3cb234ec97106b09329f8710536aff97411fec280ad1340
- Size of remote file:
- 557 MB
- SHA256:
- bafdc17eaad8703ea800d3ff993dfe0388c3f6ffb16013486aed65a5f45a13c3
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