| --- |
| license: bsd-3-clause |
| tags: |
| - image-classification |
| - vision |
| --- |
| |
| # efficientnet_b2-fp16-ov |
| |
| - Model creator: [torchvision](https://github.com/pytorch/vision) |
| - Original model: [efficientnet_b2](https://docs.pytorch.org/vision/main/models/generated/torchvision.models.efficientnet_b2.html) |
| |
| ## Description |
| |
| This is a torchvision version of [efficientnet_b2](https://docs.pytorch.org/vision/main/models/generated/torchvision.models.efficientnet_b2.html) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2026/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to FP16. |
| |
| ## Compatibility |
| |
| The provided OpenVINO™ IR model is compatible with: |
| |
| - OpenVINO version 2026.1.0 and higher |
| - Model API 0.4.0 and higher |
| |
| ## Running Model Inference with [Model API](https://github.com/open-edge-platform/model_api) |
| |
| 1. Install required packages: |
| |
| ```sh |
| pip install openvino-model-api[huggingface] |
| ``` |
| |
| <!-- markdownlint-disable MD029 --> |
| |
| 2. Run model inference: |
| |
| ```python |
| import cv2 |
| from model_api.models import Model |
| from model_api.visualizer import Visualizer |
| |
| # 1. Load model |
| model = Model.from_pretrained("OpenVINO/efficientnet_b2-fp16-ov") |
| |
| # 2. Load image |
| image = cv2.imread("image.jpg") |
| |
| # 3. Run inference |
| result = model(image) |
| |
| # 4. Visualize and save results |
| vis = Visualizer().render(image, result) |
| cv2.imwrite("output.jpg", vis) |
| ``` |
| |
| For more examples and possible optimizations, refer to the [Model API Documentation](https://open-edge-platform.github.io/model_api/latest/). |
| |
| ## Limitations |
| |
| Check the original [model implementation](https://github.com/pytorch/vision) for limitations. |
| |
| ## Legal information |
| |
| The original model is distributed under the [bsd-3-clause](https://spdx.org/licenses/BSD-3-Clause.html) license. More details can be found in [https://github.com/pytorch/vision](https://github.com/pytorch/vision). |
| |
| ## Disclaimer |
| |
| Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See [Intel’s Global Human Rights Principles](https://www.intel.com/content/dam/www/central-libraries/us/en/documents/policy-human-rights.pdf). Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights. |
| |