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")# pip install -U transformers accelerate # 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
Commit History
-
Update README.md
7696929
-
Update config.json
8fd579b -
Upload vocab.txt
7088ed8 -
Update README.md
481ef6b -
Update README.md
2ae9e4b -
Upload eval_results.txt
3d27e28 -
Upload training_args.bin with git-lfs
32685f8 -
Upload special_tokens_map.json
ff01640 -
Upload tokenizer_config.json
94af85d -
Upload config.json
bee3e3a -
Upload pytorch_model.bin with git-lfs
31a3bd8 -
initial commit
8dece46