Instructions to use allenai/multicite-multilabel-scibert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/multicite-multilabel-scibert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="allenai/multicite-multilabel-scibert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("allenai/multicite-multilabel-scibert") model = AutoModelForSequenceClassification.from_pretrained("allenai/multicite-multilabel-scibert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d92d665d2e4a940421a4f866214b61101995d322f20805087e7bc448d90f885
- Size of remote file:
- 1.34 kB
- SHA256:
- 85d25f857557348c8feb6d445e9000180542c6365133907913a327832a249371
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