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:
- e3754a7f658e2d83aece0cd24529c5b0813593968a75cc49568ed23204a6d4c7
- Size of remote file:
- 440 MB
- SHA256:
- 18171f33064f804a592cfc36b0dc8b10428dd93975cf48b0834be4bac8b002fe
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