Instructions to use wanyu/IteraTeR-ROBERTA-Intention-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wanyu/IteraTeR-ROBERTA-Intention-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="wanyu/IteraTeR-ROBERTA-Intention-Classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("wanyu/IteraTeR-ROBERTA-Intention-Classifier") model = AutoModelForSequenceClassification.from_pretrained("wanyu/IteraTeR-ROBERTA-Intention-Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 01db68a909c56261e3fa3462e035c1d3be9815e812aecd1977cddfd49613d7f5
- Size of remote file:
- 1.42 GB
- SHA256:
- 687a4f1bbdbb05208f15425e185830847334a2fd44c817164fb2ee36b6d024e5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.