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When retrieving data via ANN from Cassandra, a light-weight re-ranking for the purposes of determining what vector search results to pass the the LLM is necessary.
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## Description
Model file fit and output with v3.3.0 can not be loaded in with v4.0.0.
Tested working using lightgbm v2.3.1 and v3.3.0.
Throws exception in v4.0.0. Tested in both Windows and L…
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Hi,
When training the model using v.2.0.0 I'm getting substantially different results from v.1.7.6. Could you please clarify why this may be happening even though my code remains untouched?
I'm usin…
iftg updated
11 months ago
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Hi all,
I just did a quick naive solution based on string distance:
| Dataset | Perfect Match | In Top 10 | Recall | Loss |
| ---------- | ------------------- | ------------ | --------- | -----…
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In transformers, I directly have a method on the model to get the number of parameters, I was using the lambda rank training strategy, and I could not find a get parameters method, how do I get to kno…
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## Description
When training ranking models, LGBMRanker does not actually train. I came across this while implementing a version of LambdaMART, however in the minimum working example, I have simply u…
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## Environment info
Operating System:
Windows 10 (Same result on both Windows and WSL)
CPU/GPU model:
Intel(R) Core(TM) i7-8750H CPU @ 2.20GHz
C++/Python/R version:
Python 3.7
LightGBM…
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LightGBM version: 2.3.1
Language: C-API, via julia FFI
Platform: Linux
Context: Julia wrapper was missing support for boosting parameter (and commensurate parameters supporting it). So we worked…
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I am working on a ranking task where the labels are a mix of integers [3,2,1] and floats [0.56, 0.34, ...]. I am unable to use the dataset in its current format as Lightgbm doesn't support non-integer…