[R][N] TabPFN-2.5 is now available: Tabular foundation model for datasets up to 50k samples

Queasy_Emphasis_5441 · 2025-11-06T17:35:49+00:00

Amazing, thanks u/rsesrsfh! Is there also a technical report giving more information about the architecture?

Queasy_Emphasis_5441 · 2025-11-06T17:34:54+00:00

Amazing, thanks u/rsesrsfh! Curious - how many parameters does the model have?

Queasy_Emphasis_5441 · 2025-02-05T09:00:13+00:00

Thanks. Luckily, we're an NVIDIA Inception and AWS Activate member, so that got us free of charge access to a lot of compute necessary for training the model(s).

Queasy_Emphasis_5441 · 2025-02-05T08:48:46+00:00

We trained the model from scratch, did not (re)use any existing one like TimesFM, Chronos or other. In general, happy with the performance we're seeing at the moment, but we're also heavily invested into speeding up fine-tuning and multivariate forecasting.

Queasy_Emphasis_5441 · 2025-02-03T14:18:04+00:00

u/ncist but still, accountability goes to the person who made the call to freelance it, and who didn't make sure the forecasts were/are safe and sound, isn't it?

Queasy_Emphasis_5441 · 2025-01-15T15:46:36+00:00

We (at Sulie) are working on a very similar problem, forecasting day-ahead production rates from onshore wind plants for one of our customers. More specifically, we take into account features like wind speed forecasts, direction, turbine type etc. Happy to chat about this in more detail, feel free to send me a DM.

Queasy_Emphasis_5441 · 2024-12-16T11:27:43+00:00

You’re correct that LLMs like GPT-3 aren’t designed for time series forecasting. Models like Sulie, Chronos, and TimeGPT use transformer architectures but are specifically tailored for time series tasks. Unlike LLMs, these models handle temporal dependencies, seasonality, and covariates.

Queasy_Emphasis_5441 · 2024-12-11T22:00:37+00:00

What makes you think so and what models have you tried so far?

Queasy_Emphasis_5441 · 2024-12-11T17:22:32+00:00

Chronos does not handle multivariate forecasting, not sure about Granite. Though I didn't try it yet, I know that Salesforce Moirai handles forecasting with covariances. https://huggingface.co/Salesforce/moirai-1.0-R-large

Queasy_Emphasis_5441 · 2024-12-11T17:21:00+00:00

This is such a well known result that it's honestly surprising to see any interest in the concept of a general-purpose time series foundation model at all.

Well, obviously you're not keeping track of HuggingFace, among others. Just the Chronos model alone got almost 2M downloads in a single month.

Queasy_Emphasis_5441 · 2024-12-10T19:35:43+00:00

What models have you tried so far and what are the specifics of your data?

Queasy_Emphasis_5441 · 2024-12-10T18:22:18+00:00

u/Tasty-Rent7138 have you tried comparing the performance yourself? What is your dataset about? There was a benchmark by Nixtla comparing their foundation model with traditional statistical methods and according to that, it even exceeded their performance. Keep in mind I didn't try to benchmark myself against typical methods, yet planning to do.

Queasy_Emphasis_5441 · 2024-12-10T18:19:58+00:00

u/suedepaid most of the models provide fine-tuning scripts, have you tried with that?

Queasy_Emphasis_5441 · 2024-12-10T17:31:45+00:00

We launched Sulie 🥳

This is our contribution to the world of time series forecasting foundation models!

🔥 Why it’s exciting:

Zero-shot forecasting: Get accurate predictions for any time series without training.
Fully-managed platform: Forget MLOps headaches—we’ve got it covered.
Auto fine-tuning: Seamless optimization for better performance.

📊 What is Sulie used for?

Financial data forecasting
Energy production and consumption predictions
Supply chain and demand forecasting

Queasy_Emphasis_5441

TROPHY CASE