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Efficientnet B1 Ra4 E3600 R240 In1k FP16 Ov

Model creator: timm Original model: timm/efficientnetb1.ra4e3600r240in1k

Fuentehuggingface.co/OpenVINO/efficientnet_b1_ra4_e3600_r240_in1k-fp16-ov/tree/f71865002406f3f33ff9a6457243639cfe04c3d7
TipoOtherModelo basetimm/efficientnet_b1.ra4_e3600_r240_in1kVersiónRevision f718650Unratedcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
14,8 MB
Modelo base
timm/efficientnet_b1.ra4_e3600_r240_in1k
Versión
vRevision f718650
Actualizado
5 nov 2026
Descargas
22
Fuente
Hugging Face

Descripción de la fuente

efficientnet_b1_ra4_e3600_r240_in1k-fp16-ov

Description

This is timm/efficientnet_b1.ra4_e3600_r240_in1k model converted to the OpenVINOTM IR (Intermediate Representation) format with weights compressed to FP16.

Compatibility

The provided OpenVINOTM 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]
  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_ra4_e3600_r240_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.ra4_e3600_r240_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.

Fuentes

1 fuente
Hugging FacePrincipalVersión f71865002406f3f33ff9a6457243639cfe04c3d7
huggingface.co/OpenVINO/efficientnet_b1_ra4_e3600_r240_in1k-fp16-ov/tree/f71865002406f3f33ff9a6457243639cfe04c3d7

Verificado 5 nov

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File inventory only; completeness is unverified.

Artefactos del modelo

1 artefacto

efficientnet_b1_ra4_e3600_r240_in1k.bin

bin · 14,8 MB · SHA-256 e04feb2c9d36…7924 · Hugging Face

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Extractos de fuentes

3 extractos
Readme27 agohuggingface.co/OpenVINO/efficientnet_b1_ra4_e3600_r240_in1k-fp16-ov

--- license: apache-2.0 tags: - image-classification - vision base_model: - timm/efficientnet_b1.ra4_e3600_r240_in1k base_model_relation: finetune --- # efficientnet_b1_ra4_e3600_r240_in1k-fp16-ov - Model creator: [timm](https://huggingface.co/timm) - Original model: [timm/efficientnet_b1.ra4_e3600_r240_in1k](https://huggingface.co/timm/efficientnet_b1.ra4_e3600_r240_in1k) ## Description This is [timm/efficientnet_b1.ra4_e3600_r240_in1k](https://huggingface.co/timm/efficientnet_b1.ra4_e3600_r240_in1k) 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_b1_ra4_e3600_r240_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](https://open-edge-platform.github.io/model_api/latest/). ## Limitations Check the [original model card](https://huggingface.co/timm/efficientnet_b1.ra4_e3600_r240_in1k) for limitations. ## Legal information The original model is distributed under the [Apache-2.0](https://spdx.org/licenses/Apache-2.0.html) license. More details can be found in [timm/efficientnet_b1.ra4_e3600_r240_in1k](https://huggingface.co/timm/efficientnet_b1.ra4_e3600_r240_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](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 con...

Note5 novhuggingface.co/OpenVINO/efficientnet_b1_ra4_e3600_r240_in1k-fp16-ov

Source context: 22 downloads · 0 likes · Pipeline image-classification · Repo OpenVINO/efficientnet_b1_ra4_e3600_r240_in1k-fp16-ov

Note27 agohuggingface.co/OpenVINO/efficientnet_b1_ra4_e3600_r240_in1k-fp16-ov

Source context: 13 downloads · 0 likes · Pipeline image-classification · Repo OpenVINO/efficientnet_b1_ra4_e3600_r240_in1k-fp16-ov