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README.md

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+---
+license: bsd-3-clause
+tags:
+  - image-classification
+  - vision
+---
+
+# efficientnet_v2_m-int8-ov
+
+- Model creator: [torchvision](https://github.com/pytorch/vision)
+- Original model: [efficientnet_v2_m](https://docs.pytorch.org/vision/main/models/generated/torchvision.models.efficientnet_v2_m.html)
+
+## Description
+
+This is a torchvision version of [efficientnet_v2_m](https://docs.pytorch.org/vision/main/models/generated/torchvision.models.efficientnet_v2_m.html) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2026/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8.
+
+## Quantization Parameters
+
+Weight compression was performed using nncf.quantize with the following parameters:
+
+- **Quantization method**: Post-Training Quantization (PTQ)
+- **Precision**: INT8 for both weights and activations
+
+For more information on quantization, check the [OpenVINO model optimization guide](https://docs.openvino.ai/2026/openvino-workflow/model-optimization-guide/quantizing-models-post-training.html).
+
+## 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_v2_m-int8-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.

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