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Bump OV version (#3236) (#3256)
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‎constraints.txt

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# Openvino
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openvino==2024.6.0
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openvino==2025.0.0
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# Pytorch
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torch==2.5.1

‎docs/Installation.md

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| NNCF | OpenVINO | PyTorch | ONNX | TensorFlow | Python |
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|-----------|------------|----------|----------|------------|--------|
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| `develop` | `2024.6.0` | `2.5.1` | `1.17.0` | `2.15.1` | `3.10` |
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| `develop` | `2025.0.0` | `2.5.1` | `1.17.0` | `2.15.1` | `3.10` |
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| `2.15.0` | `2025.0.0` | `2.5.1` | `1.17.0` | `2.15.1` | `3.10` |
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| `2.14.1` | `2024.6.0` | `2.5.1` | `1.17.0` | `2.15.1` | `3.10` |
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| `2.14.0` | `2024.5.0` | `2.5.1` | `1.17.0` | `2.15.1` | `3.10` |
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| `2.13.0` | `2024.4.0` | `2.4.0` | `1.16.0` | `2.15.1` | `3.8`* |

‎examples/llm_compression/openvino/smollm2_360m_fp8/requirements.txt

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datasets
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openvino==2024.6
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openvino==2025.0
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optimum-intel[openvino]
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transformers
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onnx==1.17.0

‎examples/llm_compression/openvino/tiny_llama/requirements.txt

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transformers
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datasets==2.14.7
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openvino==2024.6
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openvino==2025.0
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optimum-intel[openvino]
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onnx==1.17.0

‎examples/llm_compression/openvino/tiny_llama_find_hyperparams/requirements.txt

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datasets
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whowhatbench @ git+https://github.com/andreyanufr/who_what_benchmark.git
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numpy>=1.23.5
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openvino==2024.6
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openvino==2025.0
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optimum-intel[openvino]>=1.13.0
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transformers>=4.35.2
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onnx==1.17.0

‎examples/llm_compression/openvino/tiny_llama_synthetic_data/requirements.txt

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torch==2.5.1
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datasets==3.0.1
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numpy>=1.23.5
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openvino==2024.6
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openvino==2025.0
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optimum-intel[openvino]>=1.13.0
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transformers>=4.35.2
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onnx==1.17.0

‎examples/post_training_quantization/onnx/mobilenet_v2/requirements.txt

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fastdownload
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onnx==1.17.0
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onnxruntime==1.19.2
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openvino==2024.6
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openvino==2025.0
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numpy<2

‎examples/post_training_quantization/onnx/yolov8_quantize_with_accuracy_control/requirements.txt

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ultralytics==8.3.22
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onnx==1.17.0
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onnxruntime==1.19.2
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openvino==2024.6
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openvino==2025.0

‎examples/post_training_quantization/openvino/anomaly_stfpm_quantize_with_accuracy_control/requirements.txt

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anomalib==0.6.0
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openvino==2024.6
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openvino==2025.0
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setuptools<=72.1.0
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numpy<2

‎examples/post_training_quantization/openvino/mobilenet_v2/requirements.txt

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tqdm
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scikit-learn
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fastdownload
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openvino==2024.6
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openvino==2025.0

‎examples/post_training_quantization/openvino/yolov8/requirements.txt

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ultralytics==8.3.22
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onnx==1.17.0
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openvino==2024.6
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openvino==2025.0

‎examples/post_training_quantization/openvino/yolov8_quantize_with_accuracy_control/requirements.txt

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ultralytics==8.3.22
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onnx==1.17.0
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openvino==2024.6
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openvino==2025.0

‎examples/post_training_quantization/tensorflow/mobilenet_v2/requirements.txt

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tensorflow==2.15.1
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tensorflow-datasets
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tqdm
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openvino==2024.6
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openvino==2025.0

‎examples/post_training_quantization/torch/mobilenet_v2/requirements.txt

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fastdownload==0.0.7
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openvino==2024.6
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openvino==2025.0
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scikit-learn
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torch==2.5.1
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torchvision==0.20.1

‎examples/post_training_quantization/torch/ssd300_vgg16/requirements.txt

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fastdownload==0.0.7
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onnx==1.17.0
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openvino==2024.6
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openvino==2025.0
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pycocotools==2.0.7
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torch==2.5.1
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torchmetrics==1.0.1

‎examples/post_training_quantization/torch_fx/resnet18/requirements.txt

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fastdownload==0.0.7
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openvino==2024.6
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openvino==2025.0
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torch==2.5.1
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torchvision==0.20.1

‎examples/quantization_aware_training/tensorflow/mobilenet_v2/requirements.txt

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tensorflow~=2.15.1; python_version >= '3.9'
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tensorflow-datasets
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tqdm
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openvino==2024.6
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openvino==2025.0

‎examples/quantization_aware_training/torch/resnet18/requirements.txt

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fastdownload==0.0.7
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openvino==2024.6
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openvino==2025.0
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torch==2.5.1
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torchvision==0.20.1
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setuptools<=72.1.0

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