jruffle

/

tabpfn_samples_32d

like 0

• "tabpfn.architectures.base.encoders.SequentialEncoder",
• "torch.nn.modules.linear.Linear",
• "tabpfn.preprocessing.definitions.PreprocessorConfig",
• "tabpfn.architectures.base.encoders.LinearInputEncoderStep",
• "tabpfn.architectures.base.encoders.VariableNumFeaturesEncoderStep",
• "tabpfn.architectures.base.config.ModelConfig",
• "torch.storage._load_from_bytes",
• "tabpfn.classifier.TabPFNClassifier",
• "joblib.numpy_pickle.NumpyArrayWrapper",
• "torch.nn.modules.container.ModuleList",
• "numpy.dtype",
• "torch._utils._rebuild_tensor_v2",
• "tabpfn.architectures.base.layer.LayerNorm",
• "torch.nn.modules.activation.GELU",
• "collections.OrderedDict",
• "torch.nn.modules.container.ModuleDict",
• "tabpfn.inference_tuning.ClassifierEvalMetrics",
• "tabpfn.architectures.base.mlp.Activation",
• "tabpfn.architectures.base.encoders.InputNormalizationEncoderStep",
• "tabpfn_extensions.embedding.tabpfn_embedding.TabPFNEmbedding",
• "numpy.ndarray",
• "tabpfn.architectures.base.mlp.MLP",
• "torch._utils._rebuild_parameter",
• "torch.device",
• "tabpfn.architectures.base.attention.full_attention.MultiHeadAttention",
• "tabpfn.architectures.base.transformer.PerFeatureTransformer",
• "tabpfn.architectures.base.thinking_tokens.AddThinkingTokens",
• "tabpfn.inference_config.InferenceConfig",
• "tabpfn.architectures.base.transformer.LayerStack",
• "tabpfn.architectures.base.layer.PerFeatureEncoderLayer",
• "tabpfn.architectures.base.encoders.MulticlassClassificationTargetEncoder",
• "tabpfn.architectures.base.encoders.NanHandlingEncoderStep",
• "tabpfn.architectures.base.encoders.RemoveEmptyFeaturesEncoderStep",
• "torch.nn.modules.container.Sequential"

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