Instructions to use uclanlp/scibart-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/scibart-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="uclanlp/scibart-large")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("uclanlp/scibart-large") model = AutoModel.from_pretrained("uclanlp/scibart-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dd715b2e5ed5c9cf1bee7fcf55a1a62f31cd2e187c53b7c7819a681b6ae15963
- Size of remote file:
- 1.54 GB
- SHA256:
- baa90dd1bec2c214ef44f44c4a9e3ae4b74d2600b3666d95fd337f880fdfda73
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