> 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/omnihub/usage.md). # Usage OmniHub exposes two entry points for loading pretrained models: the `Pretrained` facade (the recommended path for named models) and the lower-level `OmniHubUtils` class (useful when you have a filename and framework string and want direct control). *** ## The Pretrained Facade `org.eclipse.deeplearning4j.omnihub.models.Pretrained` is the simplest way to load a known model. It provides static accessor methods for the two framework namespaces: ```java import org.eclipse.deeplearning4j.omnihub.models.Pretrained; // Load the VGG19 (no-top) DL4J ComputationGraph ComputationGraph vgg19 = Pretrained.dl4j().vgg19noTop(false); // Load the AgeGoogLeNet SameDiff model SameDiff ageGooglenet = Pretrained.samediff().ageGooglenet(false); // Load ResNet18 SameDiff model SameDiff resnet18 = Pretrained.samediff().resnet18(false); ``` The boolean argument is `forceDownload`. Pass `true` to delete the cached copy and re-download even if it already exists locally. `Pretrained.dl4j()` returns a `Dl4jModels` instance. `Pretrained.samediff()` returns a `SameDiffModels` instance. Both classes are code-generated from the zoo manifest; their methods map directly to named model files. *** ## OmniHubUtils — Loading DL4J Models ### Loading a MultiLayerNetwork ```java import org.eclipse.deeplearning4j.omnihub.OmniHubUtils; import org.deeplearning4j.nn.multilayer.MultiLayerNetwork; // Load from cache (download if not cached) MultiLayerNetwork net = OmniHubUtils.loadNetwork("mymodel.zip"); // Force re-download even if cached MultiLayerNetwork net = OmniHubUtils.loadNetwork("mymodel.zip", true); ``` `loadNetwork` downloads the file from the `dl4j/` directory of the zoo, stores it in `~/.omnihub/dl4j/`, and loads it using `MultiLayerNetwork.load(file, true)` (with the parameter updater restored). ### Loading a ComputationGraph ```java import org.deeplearning4j.nn.graph.ComputationGraph; ComputationGraph graph = OmniHubUtils.loadCompGraph("vgg19_weights_tf_dim_ordering_tf_kernels_notop.zip"); // With force download ComputationGraph graph = OmniHubUtils.loadCompGraph( "vgg19_weights_tf_dim_ordering_tf_kernels_notop.zip", true ); ``` `loadCompGraph` is identical to `loadNetwork` except it calls `ComputationGraph.load(file, true)`. *** ## OmniHubUtils — Loading SameDiff Models ```java import org.nd4j.autodiff.samediff.SameDiff; SameDiff model = OmniHubUtils.loadSameDiffModel("age_googlenet.fb"); // With force download SameDiff model = OmniHubUtils.loadSameDiffModel("age_googlenet.fb", true); ``` SameDiff models are stored as FlatBuffers files (`.fb`). They are downloaded from the `samediff/` directory of the zoo and cached under `~/.omnihub/samediff/`. Loading uses `SameDiff.load(file, true)`. *** ## Direct Download with downloadAndLoadFromZoo For cases where you want the local `File` handle rather than an already-loaded model object, call `downloadAndLoadFromZoo` directly: ```java import java.io.File; File modelFile = OmniHubUtils.downloadAndLoadFromZoo( "samediff", // framework subdirectory "resnet18.fb", // filename false // forceDownload ); // Now load it yourself SameDiff sd = SameDiff.load(modelFile, true); ``` The framework string must match the subdirectory name in the zoo repository (`"dl4j"` or `"samediff"`). *** ## Caching Behavior Models are cached in the directory returned by `OmnihubConfig.getOmnihubHome()`: * Default: `~/.omnihub` * Custom: set the `OMNIHUB_HOME` environment variable before the JVM starts. The cache structure is flat per-framework: ``` ~/.omnihub/ dl4j/ vgg19_weights_tf_dim_ordering_tf_kernels_notop.zip samediff/ age_googlenet.fb resnet18.fb ``` A download is skipped if the destination file already exists (unless `forceDownload` is `true`). There is no checksum verification in the current implementation — if you suspect a file is corrupt, pass `forceDownload = true` to replace it. *** ## Overriding the Zoo URL By default, models are fetched from: ``` https://raw.githubusercontent.com/KonduitAI/omnihub-zoo/main ``` To point at a private mirror or a local HTTP server (for air-gapped environments), set the `OMNIHUB_URL` environment variable: ```bash export OMNIHUB_URL=http://internal-mirror.example.com/omnihub ``` The URL is read by `OmnihubConfig.getOmnihubUrl()` each time a download is needed. The file is resolved at: ``` ${OMNIHUB_URL}/${framework}/${name} ``` For example, `OmniHubUtils.loadSameDiffModel("resnet18.fb")` would fetch: ``` http://internal-mirror.example.com/omnihub/samediff/resnet18.fb ``` *** ## Download Progress `OmniHubUtils` wraps the download stream in a `ProgressInputStream` that prints a progress indicator to the console. The indicator is sized using an HTTP `HEAD` request to obtain the `Content-Length` before streaming begins. No configuration is needed; it activates automatically for every download. *** ## Full Example ```java import org.eclipse.deeplearning4j.omnihub.models.Pretrained; import org.deeplearning4j.nn.graph.ComputationGraph; import org.nd4j.linalg.factory.Nd4j; import org.nd4j.linalg.api.ndarray.INDArray; public class OmniHubExample { public static void main(String[] args) throws Exception { // Load VGG19 (no top layers) — downloads on first run, cached thereafter ComputationGraph vgg19 = Pretrained.dl4j().vgg19noTop(false); // VGG19 no-top expects input shape [batch, 3, 224, 224] (channels-first) INDArray input = Nd4j.rand(new int[]{1, 3, 224, 224}); INDArray[] output = vgg19.output(input); System.out.println("VGG19 feature map shape: " + output[0].shapeInfoToString()); } } ``` *** ## Next Steps * [Available Models](/omnihub/available-models.md) — full catalog of models in the zoo, with input/output details. * [OmniHub Overview](/omnihub/overview.md) — architecture, configuration, and comparison with deeplearning4j-zoo. --- # Agent Instructions This documentation is published with GitBook. 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