6.3 KiB
Nano Tutorial
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BigDL-Nano PyTorch Trainer Quickstart
In this guide we will describe how to scale out PyTorch programs using Nano Trainer
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BigDL-Nano PyTorch TorchNano Quickstart
In this guide we will describe how to use BigDL-Nano to accelerate custom training loop easily with very few changes
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BigDL-Nano TensorFlow Training Quickstart
In this guide we will describe how to accelerate TensorFlow Keras applications on training workloads with BigDL-Nano
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BigDL-Nano PyTorch ONNXRuntime Acceleration Quickstart
In this guide we will describe how to apply ONNXRuntime Acceleration on inference pipeline with the APIs delivered by BigDL-Nano
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BigDL-Nano PyTorch OpenVINO Acceleration Quickstart
In this guide we will describe how to apply OpenVINO Acceleration on inference pipeline with the APIs delivered by BigDL-Nano
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BigDL-Nano PyTorch Quantization with INC Quickstart
In this guide we will describe how to obtain a quantized model with the APIs delivered by BigDL-Nano
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BigDL-Nano PyTorch Quantization with ONNXRuntime accelerator Quickstart
In this guide we will describe how to obtain a quantized model running inference in the ONNXRuntime engine with the APIs delivered by BigDL-Nano
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BigDL-Nano PyTorch Quantization with POT Quickstart
In this guide we will describe how to obtain a quantized model with the APIs delivered by BigDL-Nano
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BigDL-Nano TensorFlow Quantization with INC Quickstart
In this guide we will demonstrates how to apply Post-training quantization on a keras model with BigDL-Nano.
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BigDL-Nano TensorFlow SparseEmbedding and SparseAdam
In this guide we demonstrates how to use SparseEmbedding and SparseAdam to obtain stroger performance with sparse gradient
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BigDL-Nano Hyperparameter Tuning (Tensorflow Sequential/Functional API) Quickstart
In this guide we will describe how to use Nano's built-in HPO utils to do hyperparameter tuning for models defined using Tensorflow Sequential or Functional API.
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BigDL-Nano Hyperparameter Tuning (Tensorflow Subclassing Model) Quickstart
In this guide we will describe how to use Nano's built-in HPO utils to do hyperparameter tuning for models defined by subclassing tf.keras.Model.