Instructions to use EhimeNLP/AcademicBART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EhimeNLP/AcademicBART with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="EhimeNLP/AcademicBART")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("EhimeNLP/AcademicBART") model = AutoModel.from_pretrained("EhimeNLP/AcademicBART") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b8c6aad35c11e263542499df46a24c8ca2cca5968ef431bc168602399bbb4e5
- Size of remote file:
- 502 MB
- SHA256:
- c3481c436d3568ea47041e51b6ad80b70a3657fcccffc1c21282da2b80fe1acd
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