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name: model-management description: "Guides TabPFN model downloads, authentication, cache behavior, save/load persistence, checkpoint conversion, visualization, and SageMaker references." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

TabPFN model management

Use this sub-skill when the user is working with checkpoint files, cache locations, browser/token access, fitted-model persistence, or the repository's checkpoint conversion and visualization helpers.

Start here

• Read references/model-overview.md for versions, path resolution, and download sources.
• Read references/model-weights.md for auth, cache, and offline behavior.
• Read references/checkpoint-utilities.md for .ckpt, .safetensors, and .tabpfn_fit workflows.
• Read references/visualization.md for regression-distribution plotting.
• Read references/sagemaker.md only if the user explicitly asks about the endpoint template.
• Read references/troubleshooting.md for access, cache, and checkpoint failures.
• Run scripts/download_models.py --help or scripts/convert_checkpoint_to_safetensors.py --help for safe local helpers.

Use this sub-skill when

• The task is about model downloads, cache directories, or browser/token authentication.
• The user wants to save or load a fitted TabPFN estimator.
• The user wants to convert a checkpoint to SafeTensors.
• The user wants to plot a regression distribution from output_type="full".
• The user wants a reference for the SageMaker endpoint example.

Route elsewhere

• Ordinary estimator use and outputs: ../tabular-prediction/SKILL.md.
• Data cleaning, category detection, or config fields: ../preprocessing-config/SKILL.md.
• Batched scoring and cache/performance behavior: ../batched-performance/SKILL.md.
• Tuning, differentiable input, or fine-tuning: ../tuning-and-advanced/SKILL.md.

What this route owns

• Model version selection and default checkpoint resolution.
• Browser/token access and local auth cache behavior.
• Download planning and offline cache recovery.
• Fitted-model save/load round trips.
• Checkpoint format conversion and visualization helpers.

What to remember

• First-use model access may require license acceptance.
• TABPFN_MODEL_CACHE_DIR and TABPFN_MODEL_CACHE_SIZE change cache behavior.
• save_fitted_tabpfn_model writes fitted estimator state, not a new foundation model.
• The SageMaker example is a template around an existing endpoint, not a default local workflow.