efficientnet_b1_pruned_in1k-fp16-ov

efficientnet_b1_pruned_in1k-fp16-ov

• Model creator: timm
• Original model: timm/efficientnet_b1_pruned.in1k

Description

This is timm/efficientnet_b1_pruned.in1k model converted to the OpenVINO™ IR (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

1. Install required packages:

pip install openvino-model-api[huggingface]

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1. Run model inference:

import cv2
from model_api.models import Model
from model_api.visualizer import Visualizer

# 1. Load model
model = Model.from_pretrained("OpenVINO/efficientnet_b1_pruned_in1k-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.

Limitations

Check the original model card for limitations.

Legal information

The original model is distributed under the Apache-2.0 license. More details can be found in timm/efficientnet_b1_pruned.in1k

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. 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.