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--- |
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library_name: onnx |
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tags: |
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- efficientnet |
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- image-classification |
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- imagenet |
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- computer-vision |
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- onnx |
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- inference4j |
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license: apache-2.0 |
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pipeline_tag: image-classification |
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--- |
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# EfficientNet-Lite4 — ONNX |
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ONNX export of [EfficientNet-Lite4](https://huggingface.co/onnx/EfficientNet-Lite4), a lightweight and efficient image classification model optimized for mobile/edge deployment. Trained on ImageNet with 1000-class output. |
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Mirrored for use with [inference4j](https://github.com/inference4j/inference4j), an inference-only AI library for Java. |
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## Original Source |
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- **Repository:** [ONNX](https://huggingface.co/onnx/EfficientNet-Lite4) |
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- **License:** apache-2.0 |
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## Usage with inference4j |
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```java |
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try (EfficientNet model = EfficientNet.fromPretrained("models/efficientnet-lite4")) { |
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List<Classification> results = model.classify(Path.of("cat.jpg")); |
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results.forEach(c -> System.out.printf("%s: %.2f%%%n", c.label(), c.score() * 100)); |
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} |
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``` |
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## Model Details |
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| Property | Value | |
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|----------|-------| |
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| Architecture | EfficientNet-Lite4 (compound-scaled CNN) | |
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| Task | Image classification (ImageNet 1000 classes) | |
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| Input | `[batch, 224, 224, 3]` — RGB, pixel values 0-255 | |
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| Output | `[batch, 1000]` — class probabilities | |
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| ONNX opset | 11 | |
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| Original framework | TensorFlow Lite → ONNX | |
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## License |
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This model is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). Original model from [ONNX](https://huggingface.co/onnx). |
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