> For the complete documentation index, see [llms.txt](https://boinc-ai.gitbook.io/optimum/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://boinc-ai.gitbook.io/optimum/overview/notebooks.md).
# Notebooks
## 🌍 Optimum notebooks
You can find here a list of the notebooks associated with each accelerator in 🌍 Optimum.
### Optimum Habana
| Notebook | Description | Colab | Studio Lab |
| ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [How to use DeepSpeed to train models with billions of parameters on Habana Gaudi](https://github.com/huggingface/optimum-habana/blob/main/notebooks/AI_HW_Summit_2022.ipynb) | Show how to use DeepSpeed to pre-train/fine-tune the 1.6B-parameter GPT2-XL for causal language modeling on Habana Gaudi. | [](https://colab.research.google.com/github/huggingface/optimum-habana/blob/main/notebooks/AI_HW_Summit_2022.ipynb) | [](https://studiolab.sagemaker.aws/import/github/huggingface/optimum-habana/blob/main/notebooks/AI_HW_Summit_2022.ipynb) |
### Optimum Intel
#### OpenVINO
| Notebook | Description | Colab | Studio Lab |
| ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [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) |
| [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) |
| [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) |
#### Neural Compressor
| Notebook | Description | Colab | Studio Lab |
| -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [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) |
### Optimum ONNX Runtime
| Notebook | Description | Colab | Studio Lab |
| --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
| [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) |
| [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) |
| [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) |
| [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) |
|
---
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## Querying This Documentation
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