Instructions to use vedu/bart-large-perturbed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vedu/bart-large-perturbed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="vedu/bart-large-perturbed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("vedu/bart-large-perturbed") model = AutoModel.from_pretrained("vedu/bart-large-perturbed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from vedu/bart-large-perturbed: direct link, hf CLI and curl.
- Browser
- Download file 813 MB
-
https://huggingface.co/vedu/bart-large-perturbed/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://vedu/bart-large-perturbed/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/vedu/bart-large-perturbed/resolve/main/flax_model.msgpack
813 MB
- Xet hash:
- 026720fd4d65229df663127dab6ced78fb230324041f3ba8ad0ef70bb23842db
- Size of remote file:
- 813 MB
- SHA256:
- 954a481dd580ea66a4c221ffc66486f2dc6850f8012e16428a4f8d45f67718f9
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