Instructions to use facebook/dpr-question_encoder-single-nq-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/dpr-question_encoder-single-nq-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/dpr-question_encoder-single-nq-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook/dpr-question_encoder-single-nq-base") model = AutoModel.from_pretrained("facebook/dpr-question_encoder-single-nq-base") - Notebooks
- Google Colab
- Kaggle
MarCognity-AI for DPR
#4
by elly99 - opened
DPR retrieves relevance.
MarCognity-AI asks: what makes relevance reflective?
https://huggingface.co/elly99/MarCognity-AI
It’s a semantic cartographer:
– Journals semantic resonance
– Scores conceptual proximity
– Reflects on the ethics of retrieval
Not just relevance.
Relevance with resonance.