Instructions to use SIRIS-Lab/citation-parser-TYPE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SIRIS-Lab/citation-parser-TYPE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SIRIS-Lab/citation-parser-TYPE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SIRIS-Lab/citation-parser-TYPE") model = AutoModelForSequenceClassification.from_pretrained("SIRIS-Lab/citation-parser-TYPE") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4e21cd6bda5730a35f52bea1b53f91d0ea1442f17d81bba6525909c60c99a7e
- Size of remote file:
- 711 MB
- SHA256:
- 3b19202bd028b39a9376277e9acf21530130881d48142cc4d79453f22ccbeb3d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.