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") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f849f23c11fa9d6b66981cda342c68e3204a1e9b372be47edd77ddf01f4a1a7f
- Size of remote file:
- 499 MB
- SHA256:
- 2188d86af150c2cd8434a1241852c8d9e17e18cc6ce972293d81015aea7fa2a2
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