Instructions to use uclanlp/scibart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/scibart-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="uclanlp/scibart-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("uclanlp/scibart-base") model = AutoModel.from_pretrained("uclanlp/scibart-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81d1fb4e7af2afc7dc5365bb8ead184d755ca39483cd4da5b56686409f7ff02e
- Size of remote file:
- 496 MB
- SHA256:
- e87b4db644829177cfb3d6c0e80ac0938db0126328cb40315803182326a2f73c
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