Instructions to use castorini/wiki-text-6-3-multi-dpr2-query-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use castorini/wiki-text-6-3-multi-dpr2-query-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="castorini/wiki-text-6-3-multi-dpr2-query-encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("castorini/wiki-text-6-3-multi-dpr2-query-encoder") model = AutoModel.from_pretrained("castorini/wiki-text-6-3-multi-dpr2-query-encoder") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1fc0d7e65aa2ffd98477a4dc405cd31e26a8a145e9127885a2edac385091dca
- Size of remote file:
- 438 MB
- SHA256:
- 1adc7ffca92df76ef662f7d498042705290ee330e332e646774f85e56c417fc1
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