Add v3 OOD checkpoints + README rows
#2
by Leogrin - opened
- README.md +2 -0
- tabpfn-v3-classifier-v3_ood.ckpt +3 -0
- tabpfn-v3-regressor-v3_ood.ckpt +3 -0
README.md
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@@ -65,6 +65,8 @@ The following specialized checkpoints are available:
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| [`tabpfn-v3-classifier-v3_20260417_multiclass.ckpt`](https://huggingface.co/Prior-Labs/tabpfn_3/blob/main/tabpfn-v3-classifier-v3_20260417_multiclass.ckpt) | Classification | Specialized for multiclass classification for datasets with <200k rows |
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| [`tabpfn-v3-regressor-v3_20260417_mediumdata.ckpt`](https://huggingface.co/Prior-Labs/tabpfn_3/blob/main/tabpfn-v3-regressor-v3_20260417_mediumdata.ckpt) | Regression | Specialized for regression for datasets with <100k rows and with alternative preprocessing |
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| [`tabpfn-v3-regressor-v3_20260506_timeseries.ckpt`](https://huggingface.co/Prior-Labs/tabpfn_3/blob/main/tabpfn-v3-regressor-v3_20260506_timeseries.ckpt) | Regression / Time-series forecasting | Fine-tuned on synthetic time-series data; used by default in TabPFN-TS-3 |
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To use one of these checkpoints, pass its filename via `model_path`:
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| [`tabpfn-v3-classifier-v3_20260417_multiclass.ckpt`](https://huggingface.co/Prior-Labs/tabpfn_3/blob/main/tabpfn-v3-classifier-v3_20260417_multiclass.ckpt) | Classification | Specialized for multiclass classification for datasets with <200k rows |
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| [`tabpfn-v3-regressor-v3_20260417_mediumdata.ckpt`](https://huggingface.co/Prior-Labs/tabpfn_3/blob/main/tabpfn-v3-regressor-v3_20260417_mediumdata.ckpt) | Regression | Specialized for regression for datasets with <100k rows and with alternative preprocessing |
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| [`tabpfn-v3-regressor-v3_20260506_timeseries.ckpt`](https://huggingface.co/Prior-Labs/tabpfn_3/blob/main/tabpfn-v3-regressor-v3_20260506_timeseries.ckpt) | Regression / Time-series forecasting | Fine-tuned on synthetic time-series data; used by default in TabPFN-TS-3 |
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| [`tabpfn-v3-classifier-v3_ood.ckpt`](https://huggingface.co/Prior-Labs/tabpfn_3/blob/main/tabpfn-v3-classifier-v3_ood.ckpt) | Classification | Useful when test inputs may fall outside the training distribution and you want the model to extrapolate. See Figure 26 in the [model report](https://arxiv.org/pdf/2605.13986). Bundles OOD-robust preprocessors (`squashing_scaler_max10` + `none`), similar to default otherwise. |
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| [`tabpfn-v3-regressor-v3_ood.ckpt`](https://huggingface.co/Prior-Labs/tabpfn_3/blob/main/tabpfn-v3-regressor-v3_ood.ckpt) | Regression | Useful when test inputs may fall outside the training distribution and you want the model to extrapolate. See Figure 26 in the [model report](https://arxiv.org/pdf/2605.13986). Bundles OOD-robust preprocessors (`quantile_uni_extrapolate` + `squashing_scaler_max10`), similar to default otherwise. |
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To use one of these checkpoints, pass its filename via `model_path`:
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tabpfn-v3-classifier-v3_ood.ckpt
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version https://git-lfs.github.com/spec/v1
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size 212815699
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tabpfn-v3-regressor-v3_ood.ckpt
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version https://git-lfs.github.com/spec/v1
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size 233300137
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