Model reference · open weights
wiki-all-8-4-multi-dpr2-passage-encoder is an open-weight embedding model from castorini. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | castorini |
|---|---|
| Type | Embedding models |
| Task | Embeddings |
| Context | 512 tokens |
| Runs with | transformers |
| Released | 2023-01-04 |
| Popularity | 7k downloads / month |
| Licence | Unknown |
About
Dense passage retriever (DPR) is a dense retrieval method described in the following paper:
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, Wen-tau Yih. Dense Passage Retrieval for Open-Domain Question Answering. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769-6781, 2020.
We have trained our own DPR models with our Wikipedia corpus variants using the Tevatron library.
Our own efforts are described in the paper entitled:
Pre-Processing Matters! Improved Wikipedia Corpora for Open-Domain Question Answering.
This is the passage encoder portion of a 2nd iteration DPR model for the wiki-all-8-4 corpus variant trained on the amalgamation of the NQ, TriviaQA, WQ, and CuratedTREC datasets.
From the published model card. Full card on the HuggingFace links in the sidebar.
Using it via the API
Once AxForge deploys wiki-all-8-4-multi-dpr2-passage-encoder for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (wiki-all-8-4-multi-dpr2-passage-encoder below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"wiki-all-8-4-multi-dpr2-passage-encoder","input":"text to embed"}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.