message: Edit Hexagon documentation to reflect new supported models
diff: @@ -22,15 +22,15 @@ are supported, including:
  **Supported models:**
  -The Hexagon delegate currently supports quantized models generated using
  -[quantization-aware training](https://github.com/tensorflow/tensorflow/tree/r1.13/tensorflow/contrib/quantize),
  -e.g.,
  -[these quantized models](https://www.tensorflow.org/lite/guide/hosted_models#quantized_models)
  -hosted on the TensorFlow Lite repo. It does not (yet) support models with
  -[8-bit symmetric quantization spec](https://www.tensorflow.org/lite/performance/quantization_spec).
  -Sample models include
  -[MobileNet V1](https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz),
  -[SSD Mobilenet](https://storage.googleapis.com/download.tensorflow.org/models/tflite/coco_ssd_mobilenet_v1_1.0_quant_2018_06_29.zip).
  +The Hexagon delegate supports all models that conform to our
  +[8-bit symmetric quantization spec](https://www.tensorflow.org/lite/performance/quantization_spec),
  +including those generated using
  +[post-training integer quantization](https://www.tensorflow.org/lite/performance/post_training_integer_quant).
  +UInt8 models trained with the legacy
  +[quantization-aware training](https://github.com/tensorflow/tensorflow/tree/r1.13/tensorflow/contrib/quantize)
  +path are also supported, for e.g.,
  +[these quantized versions](https://www.tensorflow.org/lite/guide/hosted_models#quantized_models)
  +on our Hosted Models page.
  ## Hexagon Delegate Java API
  @@ -254,10 +254,6 @@ ro.board.platform`).
  ## FAQ
  -* Will the delegate support models created using
  - [post-training quantization](https://www.tensorflow.org/lite/performance/post_training_quantization)?
  - * This is tentatively planned for a future release, though there is no
  - concrete timeline.
  * Which ops are supported by the delegate?
  * See the current list of [supported ops and constraints](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/experimental/delegates/hexagon/README.md)
  * How can I tell that the model is using the DSP when I enable the delegate?
  