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This issue is to discuss the design for the following requirements:
* the ability for the user to navigate back and forth through a session history of word lookup results
* the ability to display…
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I got this mail via the corpora list and it sound interesting
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From: Olga Uryupina
Subject: [Corpora-List] BART coreference resolver: v2.0 released
To: "corpora@uib.no"
Dear CorporaList me…
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How can we compare different approaches?
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I got this mail via the corpora list and it sound interesting
---
From: Olga Uryupina
Subject: [Corpora-List] BART coreference resolver: v2.0 released
To: "corpora@uib.no"
Dear CorporaList me…
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```
I got this mail via the corpora list and it sound interesting
---
From: Olga Uryupina
Subject: [Corpora-List] BART coreference resolver: v2.0 released
To: "corpora@uib.no"
Dear CorporaList me…
-
```
I got this mail via the corpora list and it sound interesting
---
From: Olga Uryupina
Subject: [Corpora-List] BART coreference resolver: v2.0 released
To: "corpora@uib.no"
Dear CorporaList me…
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I don't have access to openai api keys recently, to fully harness the power of my LLM-Agent with wolfram alpha, I registered the free developer wolfram engine license and consider use local LLM to do …
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Hi, I was wondering whether is would make sence to support models which, in addition to dense vectors, also support sparse and colbert. For example, [BGE-M3](https://huggingface.co/BAAI/bge-m3) works …
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```
I got this mail via the corpora list and it sound interesting
---
From: Olga Uryupina
Subject: [Corpora-List] BART coreference resolver: v2.0 released
To: "corpora@uib.no"
Dear CorporaList me…
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如题，利用以下三行代码可以实现预测
import paddlehub as hub
lac=hub.Module(name='lac')
results=lac.lexical_analysis(data=inputs)
但若我想基于另一个数据集（hub.dataset.MsraNER()）将LAC训练后再使用，该怎么做? #