-
#### “match”
Yang, Xiao, et al. "Adversarial training for community question answer selection based on multi-scale matching."
https://arxiv.org/abs/1804.08058
Kim, Seonhoon, et al. "Semantic sent…
-
Hi,
I am using one of the "Sentence similarity" models e.g. 'distilbert-base-nli-stsb-quora-ranking'
As in my domain, I am sure I have quite unique words in my use-case.
How can I handle OOV words…
-
Hi all,
The new [Performer](https://ai.googleblog.com/2020/10/rethinking-attention-with-performers.html) model may enable us to embed longer documents using the same SBERT method. HuggingFace is…
-
Hey !
So I've been using the `ARTM` model via the python API to do some topic modeling, and ran into the following bug: after training offline the model for a couple iterations, I often saw documen…
-
Hello, I have a question about the BERT encoders. In the paper, it is said that "ANCE can be used to train any dense retrieval model. For simplicity, we use a simple set up in recent research (Luan et…
-
I tried to run python do_retrieval.py -i input.fasta and received the following error:
Traceback (most recent call last):
File "/home/stcg/Documents/Dense-Homolog-Retrieval/do_retrieval.py", l…
-
首先感谢BGE提供的这么强大的模型, 我们在之前的RAG应用中, 对企业的文档通过BGE将资料转成向量存储到milvus中, 用户查询时通过dense retrieve 从milvus召回文档,我们使用的是langchain作为框架. 请问如果用BGE配合使用做 dense+sparse retrieve 有没有例子可以参考. 目前是在不知道如何进行. 万分感谢.
-
Hi Team,
Thanks for your great work and it has been a pleasure using Elasticsearch. And thank your for check my feature request among so many issue.
## Feature Description
The operations fo…
-
A100测试
code:
```
import time
from FlagEmbedding import BGEM3FlagModel
model = BGEM3FlagModel('/home/admin/bge-m3', use_fp16=True)
sentences_1 = ["What is BGE M3?", "Defination of BM25"]
…
-
Hi,
Thanks for open-sourcing this great repository!
I am trying to do inference on my own dataset. However, I don't have labeled answers for the queries. So, I can't really evaluate the method a…