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:
- 480e776d84e1423aa6c363ca5de263c93637fccbbb7dd6fcc1949dcfee189c33
- Size of remote file:
- 440 MB
- SHA256:
- 6aa7b6c930e5a67f4844386126c959a11dd53fa298690881b7ff9d94a3e07713
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