# tabpfn-mix-1.0-classifier by Autogluon: Open-Weight Model Source: https://savrn.com/models/tabpfn-mix-1-0-classifier Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- ## Runs On What it takes to serve tabpfn-mix-1.0-classifier (39M parameters): the memory its weights need at each precision, and the cheapest way to rent enough data-center GPUs to hold them. | Precision | Weights | Memory needed | Cheapest setup | Per hour | Also fits | | --- | --- | --- | --- | --- | --- | | 16-bit | 0.1 GB | 0.1 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 8-bit | 0.0 GB | 0.0 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | | 4-bit | 0.0 GB | 0.0 GB | 1x [MI300X](https://savrn.com/ai-index/pricing/gpus/mi300x) (192 GB) Vultr | $1.85 | [1x H100](https://savrn.com/ai-index/pricing/gpus/h100) $1.99 · [1x MI325X](https://savrn.com/ai-index/pricing/gpus/mi325x) $2.00 | Memory is the weights at that precision plus 20% for the runtime and a short context; a long context needs more. Prices are the lowest on-demand hourly rates in the [SAVRN Index](https://savrn.com/ai-index/pricing/gpus), read Oct 25, 2026. [tabpfn-mix-1.0-classifier on every accelerator the SAVRN Index prices, at every precision](https://savrn.com/models/tabpfn-mix-1-0-classifier/gpus) ## Model Card By Autogluon, published under apache-2.0, revision 80a938af912a. ### TabPFNMix Classifier TabPFNMix classifier is a tabular foundation model that is pre-trained on purely synthetic datasets sampled from a mix of random classifiers. ### Architecture TabPFNMix is based on a 12-layer encoder-decoder Transformer of 37 M parameters. We use a pre-training strategy incorporating in-context learning, similar to that used by TabPFN and TabForestPFN. ### Usage To use TabPFNMix classifier, install AutoGluon by running: ``` pip install autogluon ``` A minimal example showing how to perform fine-tuning and inference using the TabPFNMix classifier: ``` import pandas as pd from autogluon.tabular import TabularPredictor if __name__ == '__main__': train_data = pd.read_csv('https://autogluon.s3.amazonaws.com/datasets/Inc/train.csv') subsample_size = 5000 if subsample_size is not None and subsample_size < len(train_data): train_data = train_data.sample(n=subsample_size, random_state=0) test_data = pd.read_csv('https://autogluon.s3.amazonaws.com/datasets/Inc/test.csv') tabpfnmix_default = { "model_path_classifier": "autogluon/tabpfn-mix-1.0-classifier", "model_path_regressor": "autogluon/tabpfn-mix-1.0-regressor", "n_ensembles": 1, "max_epochs": 30, } hyperparameters = { "TABPFNMIX": [ tabpfnmix_default, ], } label = "class" predictor = TabularPredictor(label=label) predictor = predictor.fit( train_data=train_data, hyperparameters=hyperparameters, verbosity=3, ) predictor.leaderboard(test_data, display=True) ``` ### Citation [Read the full model card (260 words)](https://savrn.com/models/tabpfn-mix-1-0-classifier/card) ## Identity and Version Repository autogluon/tabpfn-mix-1.0-classifier Publisher Autogluon Task Tabular classification Modality Tabular Library Not stated by the source Parameters 39M parameters Languages Not stated by the source Revision 80a938af912a56967e8a62b8d36efba98adc116c First published 2024-11-22 Last updated 2024-11-27 ## Files and Weights 4 files, 155.8 MB in total. The weights are 1 file totalling 155.8 MB in safetensors. Weights1 file · 155.8 MB Configuration1 file · 145 B Documentation1 file · 2.7 KB Repository1 file · 1.5 KB Every file | File | Type | Size | SHA-256 | | --- | --- | --- | --- | | model.safetensors | Weights | 155.8 MB | 8c271850e1f9 | | config.json | Configuration | 145 B | — | | README.md | Documentation | 2.7 KB | — | | .gitattributes | Repository | 1.5 KB | — | ## License and Download License apache-2.0 Access Open weights, no gate Download size 155.8 MB [Download from Autogluon](https://huggingface.co/autogluon/tabpfn-mix-1.0-classifier) Released by Autogluon through its official repository on Hugging Face. [Read the license](https://www.apache.org/licenses/LICENSE-2.0). ## Built From - Described by arXiv:2003.06505 - Described by arXiv:2207.01848 - Described by arXiv:2405.13396 ## Memory Requirements | Precision | Weights in memory | | --- | --- | | As published | 155.8 MB | | 16-bit | 0.1 GB | | 8-bit | 0.0 GB | | 4-bit | 0.0 GB | Weights only, from the published parameter count; the key-value cache and runtime add to this. ## Questions About tabpfn-mix-1.0-classifier ### How much GPU memory does tabpfn-mix-1.0-classifier need? About 0.1 GB at 16-bit and 0 GB at 4-bit: the weights (39M parameters) plus a working margin. A long context needs more. ### What is the cheapest GPU to run tabpfn-mix-1.0-classifier on? At 16-bit, 1x MI300X from $1.85 an hour; at 4-bit, 1x MI300X from $1.85 an hour, at the lowest on-demand prices the SAVRN Index lists. ### Can I use tabpfn-mix-1.0-classifier commercially? Yes. tabpfn-mix-1.0-classifier is released under Apache License 2.0. The Apache License 2.0 is a permissive open-source license. It permits commercial use, modification and redistribution. 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