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**Is your feature request related to a problem? Please describe.**
Have the ability to use a LLM as a reranker in Marqo and allowing for augmented retrieval. Currently this is not supported. This can…
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Hey team,
I am looking for ways to speed a cross-encoder (`cross-encoder/ms-marco-MiniLM-L-6-v2`) on a CPU. For a variety of reasons, GPUs are off-the-table for now.
We have the following setup:…
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We need a general vector index for [RAG](https://research.ibm.com/blog/retrieval-augmented-generation-RAG). This should be general purpose and allow different data sets and content to be stored. We do…
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different scorer: `factory.scorer()`, `factory.text_scorer()` and `factory.index_scorer()` generate different embeddings for the ReRanking scenario, causing the performance difference in terms of nDCG…
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Providing examples on how to re-rank using:
- bi-encoders and cross-encoders
- Learn to rank via feature extractors
- boosting on attributes like dates, popularity
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```
Index(['parentDataset_EntityId', 'parentDataset_CatalogId', 'process_entityId',
'process_type', 'targetDataset_EntityId', 'targetDataset_CatalogId',
'parentDataset_Description', '…
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how can i add the query instruction in ChromaDB? (assuming that i use your model as ChromaDB docs explain)
should i add it simply as a prefix of the actual query? i have that doubt because for models…
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**Is your feature request related to a problem?**
We're trying to put a bunch of local model types in ml-commons (#1164). One such type is a [cross-encoder](https://www.sbert.net/examples/application…
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sorry,I want to ask if you use the re-ranking in your code, because the loss function seem the same as the ranking loss.and it seems like that you do not construct text-text fusion