Instructions to use facebook/bart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/bart-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/bart-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook/bart-base") model = AutoModel.from_pretrained("facebook/bart-base") - Inference
- Notebooks
- Google Colab
- Kaggle
typo: encoder-encoder -> encoder-decoder
#1
by dleve123 - opened
BART is an encoder-decoder, not an encoder-encoder.
It uses a standard Tranformer-based neural machine translation architecture which, despite its simplicity, can be seen as generalizing BERT (due to the bidirectional encoder), GPT (with the left-to-right decoder), and many other more recent pretraining schemes.
(https://arxiv.org/abs/1910.13461)
Great thanks!
patrickvonplaten changed pull request status to merged