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README.md

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+---
+license: agpl-3.0
+tags:
+  - object-detection
+  - vision
+base_model:
+  - Ultralytics/YOLO11
+base_model_relation: quantized
+---
+
+# YOLO11l-int8-ov
+
+- Model creator: [Ultralytics](https://huggingface.co/Ultralytics)
+- Original model: [Ultralytics/YOLO11](https://huggingface.co/Ultralytics/YOLO11)
+
+## Description
+
+This is [Ultralytics/YOLO11](https://huggingface.co/Ultralytics/YOLO11) model converted to the [OpenVINO™ IR](https://docs.openvino.ai/2026/documentation/openvino-ir-format.html) (Intermediate Representation) format with weights compressed to INT8 by [NNCF](https://github.com/openvinotoolkit/nncf).
+
+## Quantization Parameters
+
+This model was quantized using **Post-Training Quantization (PTQ)** with the following configuration:
+
+- **Quantization method**: Post-Training Quantization (PTQ)
+- **Precision**: INT8 for both weights and activations
+- **Calibration dataset**: COCO128 (128 images from COCO dataset)
+- **Framework**: Ultralytics with OpenVINO export
+
+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/YOLO11l-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 card](https://huggingface.co/Ultralytics/YOLO11) for limitations.
+
+## Legal information
+
+The original model is distributed under [GNU Affero General Public License v3.0](https://choosealicense.com/licenses/agpl-3.0/) license. More details can be found in [Ultralytics/YOLO11](https://huggingface.co/Ultralytics/YOLO11).
+
+## 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.

metadata.yaml

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+description: Ultralytics YOLO11l model trained on /ultralytics/ultralytics/cfg/datasets/coco.yaml
+author: Ultralytics
+date: '2026-04-14T13:53:42.168105'
+version: 8.4.37
+license: AGPL-3.0 License (https://ultralytics.com/license)
+docs: https://docs.ultralytics.com
+stride: 32
+task: detect
+batch: 1
+imgsz:
+- 640
+- 640
+names:
+  0: person
+  1: bicycle
+  2: car
+  3: motorcycle
+  4: airplane
+  5: bus
+  6: train
+  7: truck
+  8: boat
+  9: traffic light
+  10: fire hydrant
+  11: stop sign
+  12: parking meter
+  13: bench
+  14: bird
+  15: cat
+  16: dog
+  17: horse
+  18: sheep
+  19: cow
+  20: elephant
+  21: bear
+  22: zebra
+  23: giraffe
+  24: backpack
+  25: umbrella
+  26: handbag
+  27: tie
+  28: suitcase
+  29: frisbee
+  30: skis
+  31: snowboard
+  32: sports ball
+  33: kite
+  34: baseball bat
+  35: baseball glove
+  36: skateboard
+  37: surfboard
+  38: tennis racket
+  39: bottle
+  40: wine glass
+  41: cup
+  42: fork
+  43: knife
+  44: spoon
+  45: bowl
+  46: banana
+  47: apple
+  48: sandwich
+  49: orange
+  50: broccoli
+  51: carrot
+  52: hot dog
+  53: pizza
+  54: donut
+  55: cake
+  56: chair
+  57: couch
+  58: potted plant
+  59: bed
+  60: dining table
+  61: toilet
+  62: tv
+  63: laptop
+  64: mouse
+  65: remote
+  66: keyboard
+  67: cell phone
+  68: microwave
+  69: oven
+  70: toaster
+  71: sink
+  72: refrigerator
+  73: book
+  74: clock
+  75: vase
+  76: scissors
+  77: teddy bear
+  78: hair drier
+  79: toothbrush
+args:
+  batch: 1
+  fraction: 1.0
+  half: false
+  int8: true
+  dynamic: false
+  nms: false
+channels: 3
+end2end: false

yolo11l.bin

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