Instructions to use patrickvonplaten/bart-large-fp32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickvonplaten/bart-large-fp32 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="patrickvonplaten/bart-large-fp32")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("patrickvonplaten/bart-large-fp32") model = AutoModel.from_pretrained("patrickvonplaten/bart-large-fp32", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from patrickvonplaten/bart-large-fp32: direct link, hf CLI and curl.
- Browser
- Download file 1.63 GB
-
https://huggingface.co/patrickvonplaten/bart-large-fp32/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://patrickvonplaten/bart-large-fp32/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/patrickvonplaten/bart-large-fp32/resolve/main/flax_model.msgpack
1.63 GB
- Xet hash:
- 99f4772d577b450a649a9e793347b9a91ec6bccad921a386e767b42ac35b04f4
- Size of remote file:
- 1.63 GB
- SHA256:
- a197c46666b53bbf25f866dfb864f0067dc9716aee578a4668794407bee49a36
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