Instructions to use princeton-nlp/sup-simcse-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use princeton-nlp/sup-simcse-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="princeton-nlp/sup-simcse-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("princeton-nlp/sup-simcse-roberta-base") model = AutoModel.from_pretrained("princeton-nlp/sup-simcse-roberta-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2023d938c35d0b8213b5a3f12bc89e5a0c28bdcdbb9084a75bae4d3491b0483b
- Size of remote file:
- 499 MB
- SHA256:
- 7a542e166481b05379269f684496cd391b891e87f5adb5e4dd80ea6e5df10cb5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.