Instructions to use princeton-nlp/CoFi-RTE-s60 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use princeton-nlp/CoFi-RTE-s60 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="princeton-nlp/CoFi-RTE-s60")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("princeton-nlp/CoFi-RTE-s60") model = AutoModelForSequenceClassification.from_pretrained("princeton-nlp/CoFi-RTE-s60") - Notebooks
- Google Colab
- Kaggle
This is a model checkpoint for "Structured Pruning Learns Compact and Accurate Models". The model is pruned from bert-base-uncased to a 60% sparsity on dataset RTE. Please go to our repository for more details on how to use the model for inference. Note that you would have to use the model class specified in our repository to load the model.