> For the complete documentation index, see [llms.txt](https://deeplearning4j.konduit.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import.md).

# Model Import

- [Overview](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview.md): All model import paths in DL4J — Keras to DL4J, TF/ONNX to SameDiff, and direct inference runtimes
- [Keras Import](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1.md): Importing Keras models into Deeplearning4j — supported features, limitations, and getting started
- [Getting Started](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/getting-started.md): Step-by-step guide to importing Keras models — saving in Python, loading in Java, and running inference
- [Functional Model](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/functional-model.md): Importing Keras Functional API models as ComputationGraph
- [Sequential Model](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/sequential-model.md): Importing Keras Sequential models as MultiLayerNetwork
- [API Reference](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/model-import-api.md): KerasModelImport API — all import methods and configuration options
- [Supported Features](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/supported-features.md): Full support matrix for Keras model import — layers, activations, losses, and optimizers
- [Core Layers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/layers-core.md): DL4J equivalents and API reference for Keras core layers — Dense, Flatten, Dropout, Reshape, Merge, Permute, and more.
- [Convolutional Layers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/layers-convolutional.md): DL4J equivalents and API reference for Keras convolutional layers — Conv1D, Conv2D, Conv3D, SeparableConv2D, transposed convolutions, cropping, upsampling, and zero-padding.
- [Recurrent Layers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/layers-recurrent.md): DL4J equivalents and API reference for Keras recurrent layers — SimpleRNN, LSTM, and associated utilities.
- [Pooling Layers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/layers-pooling.md): DL4J equivalents and API reference for Keras pooling layers — MaxPooling, AveragePooling, and GlobalPooling in 1D, 2D, and 3D variants.
- [Normalization Layers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/layers-normalization.md): DL4J equivalents and API reference for Keras normalization layers — BatchNormalization.
- [Embedding Layers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/layers-embeddings.md): DL4J equivalents and API reference for Keras embedding layers — Embedding mapped to EmbeddingSequenceLayer.
- [Advanced Activations](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/layers-advanced-activations.md): DL4J equivalents and API reference for Keras advanced activation layers — LeakyReLU, PReLU, ELU, and ThresholdedReLU.
- [Wrapper Layers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/layers-wrappers.md): DL4J equivalents and API reference for Keras wrapper layers — Bidirectional and TimeDistributed.
- [Noise Layers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/layers-noise.md): DL4J equivalents and API reference for Keras noise layers — GaussianNoise, GaussianDropout, and AlphaDropout.
- [Local Layers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/layers-local.md): DL4J equivalents and API reference for Keras locally connected layers — LocallyConnected1D and LocallyConnected2D.
- [Activations](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/activations.md): Keras to DL4J activation function mapping for model import
- [Optimizers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/optimizers.md): Keras to DL4J optimizer mapping for model import
- [Losses](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/losses.md): Keras to DL4J loss function mapping for model import
- [Initializers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/initializers.md): Mapping of Keras weight initializers to DL4J WeightInit implementations for model import in Eclipse Deeplearning4j 1.0.0-rewrite.
- [Constraints](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/constraints.md): Mapping of Keras weight constraints to DL4J LayerConstraint implementations for model import in Eclipse Deeplearning4j 1.0.0-rewrite.
- [Regularizers](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/regularizers.md): Mapping of Keras regularizers to DL4J regularization for model import in Eclipse Deeplearning4j 1.0.0-rewrite.
- [Backend](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-1/backend.md): DL4J Keras model import is backend-agnostic — models trained with TensorFlow, Theano, or CNTK backends can all be imported into Eclipse Deeplearning4j 1.0.0-rewrite.
- [SameDiff Import](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-2.md): Importing TensorFlow and ONNX models into SameDiff — architecture, supported ops, and usage
- [TensorFlow Import](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-2/tensorflow.md): Importing TensorFlow frozen graphs and SavedModels into SameDiff
- [ONNX Import](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-2/onnx.md): Importing ONNX models into SameDiff
- [ONNX Import & Export (Expanded)](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-2/onnx-expanded.md): ~120 new ONNX op implementations including Microsoft LLM contrib ops, ONNX ML domain classifiers, quantized inference ops, and bidirectional SameDiff-to-ONNX export
- [GGML/GGUF Import](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-3.md): Import quantized LLMs from GGUF files — architecture handlers, quantization codecs, adaptive quantization, round-trip export, and pipeline modules
- [ONNX Runtime](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-4.md): Direct ONNX model inference via ONNX Runtime 1.10 — no conversion to SameDiff required
- [TensorFlow](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-5.md): Running TensorFlow frozen graphs directly via JavaCPP TF bindings
- [TensorFlow Lite](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-5/tensorflow-lite.md): TensorFlow Lite 2.8 inference for mobile and edge deployment
- [Apache TVM](https://deeplearning4j.konduit.ai/en-1.0.0-rewrite/model-import/overview-6.md): Apache TVM 0.8 integration for optimized model inference