Text Classification
Transformers
Safetensors
deberta-v2
citation-function-classification
scholarly-positioning
related-work-generation
rwgbench
multicite
text-embeddings-inference
Instructions to use Anonymous2876/rwgbench-citation-frame-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Anonymous2876/rwgbench-citation-frame-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Anonymous2876/rwgbench-citation-frame-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Anonymous2876/rwgbench-citation-frame-classifier") model = AutoModelForSequenceClassification.from_pretrained("Anonymous2876/rwgbench-citation-frame-classifier") - Notebooks
- Google Colab
- Kaggle
Link paper and GitHub repository
#1 opened about 21 hours ago
by
nielsr