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Hello! 😊
For my research, I'd like to integrate the AutoML framework Ludwig and the transformer TabPFN into the automlbenchmark. According to the instructions on the website, I'm starting by openin…
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https://github.com/automl/tabpfn-client/blob/c6aa6661153305f86ba009541ea997a4b77731e1/tabpfn_client/config.py#L46
Once the user has opted to re-verify email, `g_config` is initialized but `service_…
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First of all, I would like to thank you for developing TABPFN-client—it's been incredibly helpful and efficient in my projects. However, in the past few days, I’ve been encountering an issue while usi…
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I'm really looking forward to your paper on the FT-TabPFN and the release of the source code! The novel Feature Tokenisation layer sounds like a significant enhancement for handling categorical featur…
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Hi,
Thanks a lot for sharing this repo! I trained the model and evaluated on the balance-scale and mfeat-fourier datasets (the first two datasets evaluated in TabPFN). For both datasets, the model …
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When I run the demo, I get the following error:ConnectionError:
We have to download the TabPFN, as there is no checkpoint at G:\anaconda\Lib\site-packages\tabpfn\models_diff/prior_diff_real_checkpo…
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Hi, great work. I have 2 questions:
1. The results obtained are inconsistent each time. How can I set the parameters so that the random seeds of all processes are consistent and the results can be …
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I had read the paper. It is very interesting idea and a step forward from TabPFN.
Now I am looking at the MotherNet API and would like to try it on my internal data. However, it is quite frustrated s…
hqng updated
6 months ago
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There's some for-loops in the evaluation that only work if they run exactly once, which seems pretty confusing.
One is in https://github.com/automl/TabPFN/blob/main/tabpfn/RunFullDatasetAnalyses.ipyn…
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From @geoalgo:
> One thing I want to mention that I think could be quite useful is adding a way to recover original and transformed features from openml.
>
> Something like that:
```
df, y =…