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The text splitter is working well, however, parsed input in not entering the models correctly.
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My goal is to build a unique multimodal WooCommerce search experience with Vespa multivectors and an hybrid ranking on text-BM25, text-vectors, and image-vectors.
For instance, E-commerce can use:
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With the popularity of RAG, it would be great if TensorRT-LLM supported text-embedding and re-ranking models from sentence-transformers.
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![image](https://github.com/user-attachments/assets/8b2886be-25da-4b0a-a926-c96f177dab5d)
我用脚本评分后,出现的分数为零,请问这是什么情况呢?下面是我的评分代码:
import torch
from transformers import AutoModel, AutoTokenizer
mode…
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Currently the `dense_vector` field is a single-valued field. This is a limitation that forces a document to be repeated or split up into multiple documents when it's necessary to have multiple embeddi…
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**Is your feature request related to a problem? Please describe.**
Improve relevance of retrieved documents by re-ranking them using a cross-encoder
**Describe the solution you'd like**
remove distra…
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### Authur 筆者
S. Alireza Golestaneh1* Saba Dadsetan 2 Kris M. Kitani1
1 Carnegie Mellon University 2 University of Pittsburgh
### Motivation なぜやろうとしたか
transformerを導入してスコア改善を図った。
画質評価は大事よー
歪みの種類を…
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# Reranker
Re-ranking is a quick accuracy win, and as cheap computationally as sentence transformers.
Re-ranking can take account of the query as well as additional metadata when evaluating the…
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I followed your conversion here and your explanations it really help me a lot on how to implement semantic search.
https://github.com/huggingface/transformers/issues/876
I wanted your suggestio…
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Hi, my query is related to combining sentence embeddings and some external metrics. For the task of neural information retrieval, more specifically re-ranking, I have a few metrics such as page …