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Tighten OOD descriptions; drop extrapolation-mechanism and dep-version notes

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  1. README.md +2 -2
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@@ -65,8 +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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- | [`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`). |
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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`) that linearly extrapolate past the training range instead of clamping. Requires `tabpfn` from the public main branch (post-#971 merge). |
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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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