|
gptkbp:instance_of
|
gptkb:software
|
|
gptkbp:bfsLayer
|
3
|
|
gptkbp:bfsParent
|
gptkb:Graphics_Processing_Unit
|
|
gptkbp:can_be_used_with
|
gptkb:C++
gptkb:Library
|
|
gptkbp:can_create
|
flatbuffer files
optimized models
|
|
gptkbp:controls
|
multiple input formats
|
|
gptkbp:developed_by
|
gptkb:Job_Search_Engine
|
|
gptkbp:exported_to
|
gptkb:Model
Tensor Flow.js models
|
|
gptkbp:has_transformation
|
ONNX models
Keras models
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Tensor Flow Lite Converter
|
|
gptkbp:input_output
|
Tensor Flow Lite models
|
|
gptkbp:integrates_with
|
gptkb:Cloud_Computing_Service
|
|
gptkbp:is_available_in
|
gptkb:Tensor_Flow_2.x
|
|
gptkbp:is_available_on
|
gptkb:archive
|
|
gptkbp:is_compatible_with
|
gptkb:CEO
gptkb:operating_system
|
|
gptkbp:is_designed_for
|
mobile and embedded devices
|
|
gptkbp:is_documented_in
|
gptkb:archive
Tensor Flow documentation
|
|
gptkbp:is_integrated_with
|
gptkb:Tensor_Flow_Serving
|
|
gptkbp:is_open_source
|
gptkb:theorem
|
|
gptkbp:is_optimized_for
|
power consumption
inference speed
low-latency inference
models for mobile devices
|
|
gptkbp:is_part_of
|
gptkb:Research_Institute
AI development tools
machine learning workflow
Tensor Flow ecosystem
Tensor Flow Lite framework
|
|
gptkbp:is_supported_by
|
gptkb:Community_Center
Tensor Flow community
|
|
gptkbp:is_tested_for
|
real-world applications
|
|
gptkbp:is_used_by
|
gptkb:software
|
|
gptkbp:is_used_for
|
transfer learning
model deployment
model conversion
deploy models
create mobile apps
|
|
gptkbp:is_used_in
|
edge computing
AI applications
|
|
gptkbp:passes_through
|
gptkb:Raspberry_Pi
microcontrollers
|
|
gptkbp:provides
|
command line interface
quantization options
|
|
gptkbp:reduces
|
model size
|
|
gptkbp:supports
|
gptkb:multiple_platforms
hardware acceleration
real-time applications
dynamic shapes
custom operators
Tensor Flow models
|
|
gptkbp:updates
|
regularly
|