Instructions to use diarsabri/LaDPR-query-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diarsabri/LaDPR-query-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="diarsabri/LaDPR-query-encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("diarsabri/LaDPR-query-encoder") model = AutoModel.from_pretrained("diarsabri/LaDPR-query-encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d2980b96fb5ebf6cea34cae568da7b81613bdf21b44ff3976366c2f602debc3e
- Size of remote file:
- 1.88 GB
- SHA256:
- 710243a121df0718f34d93998a40a523cf8e491db2a9151b4771f66d5cac3b56
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