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|[How to run inference with the OpenVINO](https://github.com/huggingface/optimum-intel/blob/main/notebooks/openvino/optimum_openvino_inference.ipynb)| Explains how to export your model to OpenVINO and run inference with OpenVINO Runtime on various tasks|[](https://colab.research.google.com/github/huggingface/optimum-intel/blob/main/notebooks/openvino/optimum_openvino_inference.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/optimum-intel/blob/main/notebooks/openvino/optimum_openvino_inference.ipynb)|
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|[How to quantize a question answering model with OpenVINO NNCF](https://github.com/huggingface/optimum-intel/blob/main/notebooks/openvino/question_answering_quantization.ipynb)| Show how to apply post-training quantization on a question answering model using [NNCF](https://github.com/openvinotoolkit/nncf) and to accelerate inference with OpenVINO|[](https://colab.research.google.com/github/huggingface/optimum-intel/blob/main/notebooks/openvino/question_answering_quantization.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/optimum-intel/blob/main/notebooks/openvino/question_answering_quantization.ipynb)|
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|[How to run inference with OpenVINO](https://github.com/huggingface/optimum-intel/blob/main/notebooks/openvino/optimum_openvino_inference.ipynb)| Explains how to export your model to OpenVINO and run inference with OpenVINO Runtime on various tasks|[](https://colab.research.google.com/github/huggingface/optimum-intel/blob/main/notebooks/openvino/optimum_openvino_inference.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/optimum-intel/blob/main/notebooks/openvino/optimum_openvino_inference.ipynb)|
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|[How to quantize a question answering model with NNCF](https://github.com/huggingface/optimum-intel/blob/main/notebooks/openvino/question_answering_quantization.ipynb)| Show how to apply post-training quantization on a question answering model using [NNCF](https://github.com/openvinotoolkit/nncf) and to accelerate inference with OpenVINO|[](https://colab.research.google.com/github/huggingface/optimum-intel/blob/main/notebooks/openvino/question_answering_quantization.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/optimum-intel/blob/main/notebooks/openvino/question_answering_quantization.ipynb)|
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|[Compare outputs of a quantized Stable Diffusion model with its full-precision counterpart](https://github.com/huggingface/optimum-intel/blob/main/notebooks/openvino/stable_diffusion_quantization.ipynb)| Show how to load and compare outputs from two Stable Diffusion models with different precision|[](https://colab.research.google.com/github/huggingface/optimum-intel/blob/main/notebooks/openvino/stable_diffusion_quantization.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/optimum-intel/blob/main/notebooks/openvino/stable_diffusion_quantization.ipynb)|
|[How to quantize a model with Intel Neural Compressor for text classification](https://github.com/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb)| Show how to apply static, dynamic and aware training quantization on a model using Intel [Neural Compressor](https://github.com/intel/neural-compressor) for any GLUE task. |[](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb)|
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|[How to quantize a model with Intel Neural Compressor for text classification](https://github.com/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb)| Show how to apply quantization while training your model using Intel [Neural Compressor](https://github.com/intel/neural-compressor) for any GLUE task. |[](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_inc.ipynb)|
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## Optimum ONNX Runtime
@@ -45,4 +45,4 @@ You can find here a list of the notebooks associated with each accelerator in
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|[How to quantize a model with ONNX Runtime for text classification](https://github.com/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb)| Show how to apply static and dynamic quantization on a model using [ONNX Runtime](https://github.com/microsoft/onnxruntime) for any GLUE task. |[](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_quantization_ort.ipynb)|
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|[How to fine-tune a model for text classification with ONNX Runtime](https://github.com/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb)| Show how to DistilBERT model on GLUE tasks using [ONNX Runtime](https://github.com/microsoft/onnxruntime). |[](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/text_classification_ort.ipynb)|
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|[How to fine-tune a model for summarization with ONNX Runtime](https://github.com/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb)| Show how to fine-tune a T5 model on the BBC news corpus. |[](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/summarization_ort.ipynb)|
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|[How to fine-tune DeBERTa for question-answering with ONNX Runtime](https://github.com/huggingface/notebooks/blob/main/examples/question_answering_ort.ipynb)| Show how to fine-tune a DeBERTa model on the squad. |[](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/question_answering_ort.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/question_answering_ort.ipynb)|
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|[How to fine-tune DeBERTa for question-answering with ONNX Runtime](https://github.com/huggingface/notebooks/blob/main/examples/question_answering_ort.ipynb)| Show how to fine-tune a DeBERTa model on the squad. |[](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/question_answering_ort.ipynb)|[](https://studiolab.sagemaker.aws/import/github/huggingface/notebooks/blob/main/examples/question_answering_ort.ipynb)|
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