Discover and read the best of Twitter Threads about #Tabulardata
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Leave VAEs and GANs behind: LLMs are all you need for tabular data generation!
We introduce a new method GReaT (Generation of Realistic Tabular data), with state-of-the-art generative abilities (see below). How we did it? ↓ (1/n)
#tabulardata
We introduce a new method GReaT (Generation of Realistic Tabular data), with state-of-the-art generative abilities (see below). How we did it? ↓ (1/n)
#tabulardata
(2/n) Tabular data frequently consists of categorical and numerical data. Furthermore, categorical data and feature names typically are words. Thus, it is possible to represent a tabular data sample as a meaningful sentence, e.g., "Age is 42, Education is HS-grad, ..."
(3/n) ... where feature name and value are used together. After this step, we can fine-tune a pre-trained large language model (LLM) on obtained sentences, and use the LLM to synthesise new data samples!
#AutoGluon 0.4 is officially released. It's a big update with better performance (up to 90% win rate), better speed (up to 2x faster), removed dependencies, more compatibility (full Windows support), and more models. 151 commits from 14 contributors. auto.gluon.ai 🧵 1/
To get started on #Windows follow the instructions at auto.gluon.ai/0.4.0/index.ht… - TL;DR 1) Install Anaconda; 2) Install Python 3.9, pip and wheel; 3) pip install PyTorch 1.10.1; 4) pip install autogluon. 2/
Text support got a massive upgrade. It now supports @huggingface transformer backbones and uses @PyTorchLightnin. Relative to the 0.3 release arxiv.org/abs/2111.02705, the 0.4 release has an over 70% win rate. We support multiple languages and transfer learning. 3/
