Instructions to use vblagoje/dpr-question_encoder-single-lfqa-wiki with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vblagoje/dpr-question_encoder-single-lfqa-wiki with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="vblagoje/dpr-question_encoder-single-lfqa-wiki")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("vblagoje/dpr-question_encoder-single-lfqa-wiki") model = AutoModel.from_pretrained("vblagoje/dpr-question_encoder-single-lfqa-wiki") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 894192cf25ca05569fcfc5b71709bcbd1adc848d903a8740464afe20b82792f4
- Size of remote file:
- 438 MB
- SHA256:
- 06ecf256fa17e04a92486d4590037d016210c74af98c9ab5260b80b026aedf25
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