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")# 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
- Xet hash:
- c52e926f1269cd2a318e8179b72089acc2acc59a41472f4a67835f50cc5b5ecb
- Size of remote file:
- 1.63 GB
- SHA256:
- 167f36942ef5dd4ba793495a9212715ddef9a34085fb114f2768ce0aff3fe783
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