Optimum
  • 🌍OVERVIEW
    • Optimum
    • Installation
    • Quick tour
    • Notebooks
    • 🌍CONCEPTUAL GUIDES
      • Quantization
  • 🌍HABANA
    • BOINC AI Optimum Habana
    • Installation
    • Quickstart
    • 🌍TUTORIALS
      • Overview
      • Single-HPU Training
      • Distributed Training
      • Run Inference
      • Stable Diffusion
      • LDM3D
    • 🌍HOW-TO GUIDES
      • Overview
      • Pretraining Transformers
      • Accelerating Training
      • Accelerating Inference
      • How to use DeepSpeed
      • Multi-node Training
    • 🌍CONCEPTUAL GUIDES
      • What are Habana's Gaudi and HPUs?
    • 🌍REFERENCE
      • Gaudi Trainer
      • Gaudi Configuration
      • Gaudi Stable Diffusion Pipeline
      • Distributed Runner
  • 🌍INTEL
    • BOINC AI Optimum Intel
    • Installation
    • 🌍NEURAL COMPRESSOR
      • Optimization
      • Distributed Training
      • Reference
    • 🌍OPENVINO
      • Models for inference
      • Optimization
      • Reference
  • 🌍AWS TRAINIUM/INFERENTIA
    • BOINC AI Optimum Neuron
  • 🌍FURIOSA
    • BOINC AI Optimum Furiosa
    • Installation
    • 🌍HOW-TO GUIDES
      • Overview
      • Modeling
      • Quantization
    • 🌍REFERENCE
      • Models
      • Configuration
      • Quantization
  • 🌍ONNX RUNTIME
    • Overview
    • Quick tour
    • 🌍HOW-TO GUIDES
      • Inference pipelines
      • Models for inference
      • How to apply graph optimization
      • How to apply dynamic and static quantization
      • How to accelerate training
      • Accelerated inference on NVIDIA GPUs
    • 🌍CONCEPTUAL GUIDES
      • ONNX And ONNX Runtime
    • 🌍REFERENCE
      • ONNX Runtime Models
      • Configuration
      • Optimization
      • Quantization
      • Trainer
  • 🌍EXPORTERS
    • Overview
    • The TasksManager
    • 🌍ONNX
      • Overview
      • 🌍HOW-TO GUIDES
        • Export a model to ONNX
        • Add support for exporting an architecture to ONNX
      • 🌍REFERENCE
        • ONNX configurations
        • Export functions
    • 🌍TFLITE
      • Overview
      • 🌍HOW-TO GUIDES
        • Export a model to TFLite
        • Add support for exporting an architecture to TFLite
      • 🌍REFERENCE
        • TFLite configurations
        • Export functions
  • 🌍TORCH FX
    • Overview
    • 🌍HOW-TO GUIDES
      • Optimization
    • 🌍CONCEPTUAL GUIDES
      • Symbolic tracer
    • 🌍REFERENCE
      • Optimization
  • 🌍BETTERTRANSFORMER
    • Overview
    • 🌍TUTORIALS
      • Convert Transformers models to use BetterTransformer
      • How to add support for new architectures?
  • 🌍LLM QUANTIZATION
    • GPTQ quantization
  • 🌍UTILITIES
    • Dummy input generators
    • Normalized configurations
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  1. EXPORTERS
  2. TFLITE

Overview

Overview

🌍 Optimum handles the export of TensorFlow models to TFLite in the exporters.tflite module. In addition, models hosted on the Hugging Face Hub with PyTorch weights but having a TensorFlow implementation will also be supported in the export thanks to Transformers’ TFPreTrainedModel.from_pretrained() auto-conversion to TensorFlow.

The TFLite export support provides classes, functions and a command line interface to export a model easily.

Supported architectures:

  • Albert

  • BERT

  • Camembert

  • ConvBert

  • Deberta

  • Deberta V2

  • DistilBert

  • Electra

  • Flaubert

  • MobileBert

  • MPNet

  • ResNet

  • Roberta

  • RoFormer

  • XLM

  • XLMRoberta

PreviousTFLITENextHOW-TO GUIDES

Last updated 1 year ago

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